mirror of
https://github.com/oobabooga/text-generation-webui.git
synced 2024-09-20 10:35:10 +02:00
Merge branch 'main' into main
This commit is contained in:
Alexander Hristov Hristov
GitHub
commit
63c5a139a2
10 changed files with 158 additions and 81 deletions
1
.github/FUNDING.yml
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1
.github/FUNDING.yml
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@ -0,0 +1 @@
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ko_fi: oobabooga
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23
README.md
23
README.md
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@ -27,7 +27,7 @@ Its goal is to become the [AUTOMATIC1111/stable-diffusion-webui](https://github.
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* [FlexGen offload](https://github.com/oobabooga/text-generation-webui/wiki/FlexGen).
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* [DeepSpeed ZeRO-3 offload](https://github.com/oobabooga/text-generation-webui/wiki/DeepSpeed).
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* Get responses via API, [with](https://github.com/oobabooga/text-generation-webui/blob/main/api-example-streaming.py) or [without](https://github.com/oobabooga/text-generation-webui/blob/main/api-example.py) streaming.
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* [Supports the LLaMA model](https://github.com/oobabooga/text-generation-webui/wiki/LLaMA-model).
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* [Supports the LLaMA model, including 4-bit mode](https://github.com/oobabooga/text-generation-webui/wiki/LLaMA-model).
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* [Supports the RWKV model](https://github.com/oobabooga/text-generation-webui/wiki/RWKV-model).
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* Supports softprompts.
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* [Supports extensions](https://github.com/oobabooga/text-generation-webui/wiki/Extensions).
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@ -60,11 +60,13 @@ pip3 install torch torchvision torchaudio --extra-index-url https://download.pyt
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conda install pytorch torchvision torchaudio git -c pytorch
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```
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See also: [Installation instructions for human beings](https://github.com/oobabooga/text-generation-webui/wiki/Installation-instructions-for-human-beings).
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## Installation option 2: one-click installers
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[oobabooga-windows.zip](https://github.com/oobabooga/text-generation-webui/releases/download/installers/oobabooga-windows.zip)
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[oobabooga-windows.zip](https://github.com/oobabooga/one-click-installers/archive/refs/heads/oobabooga-windows.zip)
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[oobabooga-linux.zip](https://github.com/oobabooga/text-generation-webui/releases/download/installers/oobabooga-linux.zip)
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[oobabooga-linux.zip](https://github.com/oobabooga/one-click-installers/archive/refs/heads/oobabooga-linux.zip)
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Just download the zip above, extract it, and double click on "install". The web UI and all its dependencies will be installed in the same folder.
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@ -139,7 +141,7 @@ Optionally, you can use the following command-line flags:
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| `--cpu` | Use the CPU to generate text.|
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| `--load-in-8bit` | Load the model with 8-bit precision.|
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| `--load-in-4bit` | Load the model with 4-bit precision. Currently only works with LLaMA.|
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| `--gptq-bits` | Load a pre-quantized model with specified precision. 2, 3, 4 and 8bit are supported. Currently only works with LLaMA. |
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| `--gptq-bits GPTQ_BITS` | Load a pre-quantized model with specified precision. 2, 3, 4 and 8 (bit) are supported. Currently only works with LLaMA. |
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| `--bf16` | Load the model with bfloat16 precision. Requires NVIDIA Ampere GPU. |
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| `--auto-devices` | Automatically split the model across the available GPU(s) and CPU.|
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| `--disk` | If the model is too large for your GPU(s) and CPU combined, send the remaining layers to the disk. |
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@ -155,12 +157,13 @@ Optionally, you can use the following command-line flags:
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| `--local_rank LOCAL_RANK` | DeepSpeed: Optional argument for distributed setups. |
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| `--rwkv-strategy RWKV_STRATEGY` | RWKV: The strategy to use while loading the model. Examples: "cpu fp32", "cuda fp16", "cuda fp16i8". |
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| `--rwkv-cuda-on` | RWKV: Compile the CUDA kernel for better performance. |
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| `--no-stream` | Don't stream the text output in real time. This improves the text generation performance.|
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| `--no-stream` | Don't stream the text output in real time. |
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| `--settings SETTINGS_FILE` | Load the default interface settings from this json file. See `settings-template.json` for an example. If you create a file called `settings.json`, this file will be loaded by default without the need to use the `--settings` flag.|
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| `--extensions EXTENSIONS [EXTENSIONS ...]` | The list of extensions to load. If you want to load more than one extension, write the names separated by spaces. |
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| `--listen` | Make the web UI reachable from your local network.|
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| `--listen-port LISTEN_PORT` | The listening port that the server will use. |
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| `--share` | Create a public URL. This is useful for running the web UI on Google Colab or similar. |
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| `--auto-launch` | Open the web UI in the default browser upon launch. |
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| `--verbose` | Print the prompts to the terminal. |
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Out of memory errors? [Check this guide](https://github.com/oobabooga/text-generation-webui/wiki/Low-VRAM-guide).
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@ -179,14 +182,10 @@ Check the [wiki](https://github.com/oobabooga/text-generation-webui/wiki/System-
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Pull requests, suggestions, and issue reports are welcome.
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Before reporting a bug, make sure that you have created a conda environment and installed the dependencies exactly as in the *Installation* section above.
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Before reporting a bug, make sure that you have:
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These issues are known:
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* 8-bit doesn't work properly on Windows or older GPUs.
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* DeepSpeed doesn't work properly on Windows.
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For these two, please try commenting on an existing issue instead of creating a new one.
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1. Created a conda environment and installed the dependencies exactly as in the *Installation* section above.
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2. [Searched](https://github.com/oobabooga/text-generation-webui/issues) to see if an issue already exists for the issue you encountered.
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## Credits
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@ -1,8 +1,12 @@
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import time
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from pathlib import Path
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import gradio as gr
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import torch
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import modules.chat as chat
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import modules.shared as shared
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torch._C._jit_set_profiling_mode(False)
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params = {
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@ -12,10 +16,28 @@ params = {
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'model_id': 'v3_en',
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'sample_rate': 48000,
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'device': 'cpu',
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'show_text': False,
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'autoplay': True,
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'voice_pitch': 'medium',
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'voice_speed': 'medium',
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}
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current_params = params.copy()
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voices_by_gender = ['en_99', 'en_45', 'en_18', 'en_117', 'en_49', 'en_51', 'en_68', 'en_0', 'en_26', 'en_56', 'en_74', 'en_5', 'en_38', 'en_53', 'en_21', 'en_37', 'en_107', 'en_10', 'en_82', 'en_16', 'en_41', 'en_12', 'en_67', 'en_61', 'en_14', 'en_11', 'en_39', 'en_52', 'en_24', 'en_97', 'en_28', 'en_72', 'en_94', 'en_36', 'en_4', 'en_43', 'en_88', 'en_25', 'en_65', 'en_6', 'en_44', 'en_75', 'en_91', 'en_60', 'en_109', 'en_85', 'en_101', 'en_108', 'en_50', 'en_96', 'en_64', 'en_92', 'en_76', 'en_33', 'en_116', 'en_48', 'en_98', 'en_86', 'en_62', 'en_54', 'en_95', 'en_55', 'en_111', 'en_3', 'en_83', 'en_8', 'en_47', 'en_59', 'en_1', 'en_2', 'en_7', 'en_9', 'en_13', 'en_15', 'en_17', 'en_19', 'en_20', 'en_22', 'en_23', 'en_27', 'en_29', 'en_30', 'en_31', 'en_32', 'en_34', 'en_35', 'en_40', 'en_42', 'en_46', 'en_57', 'en_58', 'en_63', 'en_66', 'en_69', 'en_70', 'en_71', 'en_73', 'en_77', 'en_78', 'en_79', 'en_80', 'en_81', 'en_84', 'en_87', 'en_89', 'en_90', 'en_93', 'en_100', 'en_102', 'en_103', 'en_104', 'en_105', 'en_106', 'en_110', 'en_112', 'en_113', 'en_114', 'en_115']
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wav_idx = 0
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voice_pitches = ['x-low', 'low', 'medium', 'high', 'x-high']
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voice_speeds = ['x-slow', 'slow', 'medium', 'fast', 'x-fast']
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# Used for making text xml compatible, needed for voice pitch and speed control
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table = str.maketrans({
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"<": "<",
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">": ">",
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"&": "&",
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"'": "'",
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'"': """,
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})
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def xmlesc(txt):
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return txt.translate(table)
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def load_model():
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model, example_text = torch.hub.load(repo_or_dir='snakers4/silero-models', model='silero_tts', language=params['language'], speaker=params['model_id'])
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@ -33,12 +55,32 @@ def remove_surrounded_chars(string):
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new_string += char
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return new_string
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def remove_tts_from_history(name1, name2):
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for i, entry in enumerate(shared.history['internal']):
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shared.history['visible'][i] = [shared.history['visible'][i][0], entry[1]]
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return chat.generate_chat_output(shared.history['visible'], name1, name2, shared.character)
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def toggle_text_in_history(name1, name2):
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for i, entry in enumerate(shared.history['visible']):
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visible_reply = entry[1]
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if visible_reply.startswith('<audio'):
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if params['show_text']:
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reply = shared.history['internal'][i][1]
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shared.history['visible'][i] = [shared.history['visible'][i][0], f"{visible_reply.split('</audio>')[0]}</audio>\n\n{reply}"]
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else:
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shared.history['visible'][i] = [shared.history['visible'][i][0], f"{visible_reply.split('</audio>')[0]}</audio>"]
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return chat.generate_chat_output(shared.history['visible'], name1, name2, shared.character)
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def input_modifier(string):
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"""
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This function is applied to your text inputs before
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they are fed into the model.
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"""
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# Remove autoplay from the last reply
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if (shared.args.chat or shared.args.cai_chat) and len(shared.history['internal']) > 0:
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shared.history['visible'][-1] = [shared.history['visible'][-1][0], shared.history['visible'][-1][1].replace('controls autoplay>','controls>')]
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return string
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def output_modifier(string):
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@ -46,7 +88,7 @@ def output_modifier(string):
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This function is applied to the model outputs.
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"""
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global wav_idx, model, current_params
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global model, current_params
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for i in params:
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if params[i] != current_params[i]:
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@ -57,6 +99,7 @@ def output_modifier(string):
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if params['activate'] == False:
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return string
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original_string = string
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string = remove_surrounded_chars(string)
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string = string.replace('"', '')
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string = string.replace('“', '')
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@ -64,13 +107,17 @@ def output_modifier(string):
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string = string.strip()
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if string == '':
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string = 'empty reply, try regenerating'
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string = '*Empty reply, try regenerating*'
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else:
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output_file = Path(f'extensions/silero_tts/outputs/{shared.character}_{int(time.time())}.wav')
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prosody = '<prosody rate="{}" pitch="{}">'.format(params['voice_speed'], params['voice_pitch'])
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silero_input = f'<speak>{prosody}{xmlesc(string)}</prosody></speak>'
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model.save_wav(ssml_text=silero_input, speaker=params['speaker'], sample_rate=int(params['sample_rate']), audio_path=str(output_file))
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output_file = Path(f'extensions/silero_tts/outputs/{wav_idx:06d}.wav')
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model.save_wav(text=string, speaker=params['speaker'], sample_rate=int(params['sample_rate']), audio_path=str(output_file))
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string = f'<audio src="file/{output_file.as_posix()}" controls></audio>'
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wav_idx += 1
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autoplay = 'autoplay' if params['autoplay'] else ''
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string = f'<audio src="file/{output_file.as_posix()}" controls {autoplay}></audio>'
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if params['show_text']:
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string += f'\n\n{original_string}'
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return string
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@ -85,9 +132,36 @@ def bot_prefix_modifier(string):
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def ui():
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# Gradio elements
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activate = gr.Checkbox(value=params['activate'], label='Activate TTS')
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voice = gr.Dropdown(value=params['speaker'], choices=voices_by_gender, label='TTS voice')
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with gr.Accordion("Silero TTS"):
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with gr.Row():
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activate = gr.Checkbox(value=params['activate'], label='Activate TTS')
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autoplay = gr.Checkbox(value=params['autoplay'], label='Play TTS automatically')
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show_text = gr.Checkbox(value=params['show_text'], label='Show message text under audio player')
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voice = gr.Dropdown(value=params['speaker'], choices=voices_by_gender, label='TTS voice')
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with gr.Row():
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v_pitch = gr.Dropdown(value=params['voice_pitch'], choices=voice_pitches, label='Voice pitch')
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v_speed = gr.Dropdown(value=params['voice_speed'], choices=voice_speeds, label='Voice speed')
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with gr.Row():
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convert = gr.Button('Permanently replace audios with the message texts')
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convert_cancel = gr.Button('Cancel', visible=False)
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convert_confirm = gr.Button('Confirm (cannot be undone)', variant="stop", visible=False)
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# Convert history with confirmation
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convert_arr = [convert_confirm, convert, convert_cancel]
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convert.click(lambda :[gr.update(visible=True), gr.update(visible=False), gr.update(visible=True)], None, convert_arr)
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convert_confirm.click(lambda :[gr.update(visible=False), gr.update(visible=True), gr.update(visible=False)], None, convert_arr)
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convert_confirm.click(remove_tts_from_history, [shared.gradio['name1'], shared.gradio['name2']], shared.gradio['display'])
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convert_confirm.click(lambda : chat.save_history(timestamp=False), [], [], show_progress=False)
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convert_cancel.click(lambda :[gr.update(visible=False), gr.update(visible=True), gr.update(visible=False)], None, convert_arr)
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# Toggle message text in history
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show_text.change(lambda x: params.update({"show_text": x}), show_text, None)
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show_text.change(toggle_text_in_history, [shared.gradio['name1'], shared.gradio['name2']], shared.gradio['display'])
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show_text.change(lambda : chat.save_history(timestamp=False), [], [], show_progress=False)
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# Event functions to update the parameters in the backend
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activate.change(lambda x: params.update({"activate": x}), activate, None)
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autoplay.change(lambda x: params.update({"autoplay": x}), autoplay, None)
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voice.change(lambda x: params.update({"speaker": x}), voice, None)
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v_pitch.change(lambda x: params.update({"voice_pitch": x}), v_pitch, None)
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v_speed.change(lambda x: params.update({"voice_speed": x}), v_speed, None)
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|
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@ -25,10 +25,10 @@ class RWKVModel:
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tokenizer_path = Path(f"{path.parent}/20B_tokenizer.json")
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if shared.args.rwkv_strategy is None:
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model = RWKV(model=os.path.abspath(path), strategy=f'{device} {dtype}')
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model = RWKV(model=str(path), strategy=f'{device} {dtype}')
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else:
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model = RWKV(model=os.path.abspath(path), strategy=shared.args.rwkv_strategy)
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pipeline = PIPELINE(model, os.path.abspath(tokenizer_path))
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model = RWKV(model=str(path), strategy=shared.args.rwkv_strategy)
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pipeline = PIPELINE(model, str(tokenizer_path))
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result = self()
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result.pipeline = pipeline
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@ -61,7 +61,7 @@ class RWKVTokenizer:
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@classmethod
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def from_pretrained(self, path):
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tokenizer_path = path / "20B_tokenizer.json"
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tokenizer = Tokenizer.from_file(os.path.abspath(tokenizer_path))
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tokenizer = Tokenizer.from_file(str(tokenizer_path))
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||||
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||||
result = self()
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result.tokenizer = tokenizer
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|
|
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@ -22,6 +22,12 @@ def clean_chat_message(text):
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text = text.strip()
|
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return text
|
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def generate_chat_output(history, name1, name2, character):
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if shared.args.cai_chat:
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return generate_chat_html(history, name1, name2, character)
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else:
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return history
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|
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def generate_chat_prompt(user_input, max_new_tokens, name1, name2, context, chat_prompt_size, impersonate=False):
|
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user_input = clean_chat_message(user_input)
|
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rows = [f"{context.strip()}\n"]
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@ -53,7 +59,6 @@ def generate_chat_prompt(user_input, max_new_tokens, name1, name2, context, chat
|
|||
|
||||
def extract_message_from_reply(question, reply, name1, name2, check, impersonate=False):
|
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next_character_found = False
|
||||
substring_found = False
|
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|
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asker = name1 if not impersonate else name2
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replier = name2 if not impersonate else name1
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@ -79,15 +84,15 @@ def extract_message_from_reply(question, reply, name1, name2, check, impersonate
|
|||
next_character_found = True
|
||||
reply = clean_chat_message(reply)
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|
||||
# Detect if something like "\nYo" is generated just before
|
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# "\nYou:" is completed
|
||||
tmp = f"\n{asker}:"
|
||||
for j in range(1, len(tmp)):
|
||||
if reply[-j:] == tmp[:j]:
|
||||
# If something like "\nYo" is generated just before "\nYou:"
|
||||
# is completed, trim it
|
||||
next_turn = f"\n{asker}:"
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||||
for j in range(len(next_turn)-1, 0, -1):
|
||||
if reply[-j:] == next_turn[:j]:
|
||||
reply = reply[:-j]
|
||||
substring_found = True
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break
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||||
|
||||
return reply, next_character_found, substring_found
|
||||
return reply, next_character_found
|
||||
|
||||
def stop_everything_event():
|
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shared.stop_everything = True
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||||
|
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@ -122,7 +127,6 @@ def chatbot_wrapper(text, max_new_tokens, do_sample, temperature, top_p, typical
|
|||
prompt = custom_generate_chat_prompt(text, max_new_tokens, name1, name2, context, chat_prompt_size)
|
||||
|
||||
if not regenerate:
|
||||
# Display user input and "*is typing...*" imediately
|
||||
yield shared.history['visible']+[[visible_text, '*Is typing...*']]
|
||||
|
||||
# Generate
|
||||
|
|
@ -131,7 +135,7 @@ def chatbot_wrapper(text, max_new_tokens, do_sample, temperature, top_p, typical
|
|||
for reply in generate_reply(f"{prompt}{' ' if len(reply) > 0 else ''}{reply}", max_new_tokens, do_sample, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, eos_token=eos_token, stopping_string=f"\n{name1}:"):
|
||||
|
||||
# Extracting the reply
|
||||
reply, next_character_found, substring_found = extract_message_from_reply(prompt, reply, name1, name2, check)
|
||||
reply, next_character_found = extract_message_from_reply(prompt, reply, name1, name2, check)
|
||||
visible_reply = re.sub("(<USER>|<user>|{{user}})", name1_original, reply)
|
||||
visible_reply = apply_extensions(visible_reply, "output")
|
||||
if shared.args.chat:
|
||||
|
|
@ -148,7 +152,7 @@ def chatbot_wrapper(text, max_new_tokens, do_sample, temperature, top_p, typical
|
|||
|
||||
shared.history['internal'][-1] = [text, reply]
|
||||
shared.history['visible'][-1] = [visible_text, visible_reply]
|
||||
if not substring_found and not shared.args.no_stream:
|
||||
if not shared.args.no_stream:
|
||||
yield shared.history['visible']
|
||||
if next_character_found:
|
||||
break
|
||||
|
|
@ -163,15 +167,12 @@ def impersonate_wrapper(text, max_new_tokens, do_sample, temperature, top_p, typ
|
|||
|
||||
prompt = generate_chat_prompt(text, max_new_tokens, name1, name2, context, chat_prompt_size, impersonate=True)
|
||||
|
||||
# Display "*is typing...*" imediately
|
||||
yield '*Is typing...*'
|
||||
|
||||
reply = ''
|
||||
yield '*Is typing...*'
|
||||
for i in range(chat_generation_attempts):
|
||||
for reply in generate_reply(prompt+reply, max_new_tokens, do_sample, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, eos_token=eos_token, stopping_string=f"\n{name2}:"):
|
||||
reply, next_character_found, substring_found = extract_message_from_reply(prompt, reply, name1, name2, check, impersonate=True)
|
||||
if not substring_found:
|
||||
yield reply
|
||||
reply, next_character_found = extract_message_from_reply(prompt, reply, name1, name2, check, impersonate=True)
|
||||
yield reply
|
||||
if next_character_found:
|
||||
break
|
||||
yield reply
|
||||
|
|
@ -182,21 +183,18 @@ def cai_chatbot_wrapper(text, max_new_tokens, do_sample, temperature, top_p, typ
|
|||
|
||||
def regenerate_wrapper(text, max_new_tokens, do_sample, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, name1, name2, context, check, chat_prompt_size, chat_generation_attempts=1):
|
||||
if (shared.character != 'None' and len(shared.history['visible']) == 1) or len(shared.history['internal']) == 0:
|
||||
if shared.args.cai_chat:
|
||||
yield generate_chat_html(shared.history['visible'], name1, name2, shared.character)
|
||||
else:
|
||||
yield shared.history['visible']
|
||||
yield generate_chat_output(shared.history['visible'], name1, name2, shared.character)
|
||||
else:
|
||||
last_visible = shared.history['visible'].pop()
|
||||
last_internal = shared.history['internal'].pop()
|
||||
|
||||
yield generate_chat_output(shared.history['visible']+[[last_visible[0], '*Is typing...*']], name1, name2, shared.character)
|
||||
for _history in chatbot_wrapper(last_internal[0], max_new_tokens, do_sample, temperature, top_p, typical_p, repetition_penalty, top_k, min_length, no_repeat_ngram_size, num_beams, penalty_alpha, length_penalty, early_stopping, name1, name2, context, check, chat_prompt_size, chat_generation_attempts, regenerate=True):
|
||||
if shared.args.cai_chat:
|
||||
shared.history['visible'][-1] = [last_visible[0], _history[-1][1]]
|
||||
yield generate_chat_html(shared.history['visible'], name1, name2, shared.character)
|
||||
else:
|
||||
shared.history['visible'][-1] = (last_visible[0], _history[-1][1])
|
||||
yield shared.history['visible']
|
||||
yield generate_chat_output(shared.history['visible'], name1, name2, shared.character)
|
||||
|
||||
def remove_last_message(name1, name2):
|
||||
if len(shared.history['visible']) > 0 and not shared.history['internal'][-1][0] == '<|BEGIN-VISIBLE-CHAT|>':
|
||||
|
|
@ -204,6 +202,7 @@ def remove_last_message(name1, name2):
|
|||
shared.history['internal'].pop()
|
||||
else:
|
||||
last = ['', '']
|
||||
|
||||
if shared.args.cai_chat:
|
||||
return generate_chat_html(shared.history['visible'], name1, name2, shared.character), last[0]
|
||||
else:
|
||||
|
|
@ -223,10 +222,7 @@ def replace_last_reply(text, name1, name2):
|
|||
shared.history['visible'][-1] = (shared.history['visible'][-1][0], text)
|
||||
shared.history['internal'][-1][1] = apply_extensions(text, "input")
|
||||
|
||||
if shared.args.cai_chat:
|
||||
return generate_chat_html(shared.history['visible'], name1, name2, shared.character)
|
||||
else:
|
||||
return shared.history['visible']
|
||||
return generate_chat_output(shared.history['visible'], name1, name2, shared.character)
|
||||
|
||||
def clear_html():
|
||||
return generate_chat_html([], "", "", shared.character)
|
||||
|
|
@ -246,10 +242,8 @@ def clear_chat_log(name1, name2):
|
|||
else:
|
||||
shared.history['internal'] = []
|
||||
shared.history['visible'] = []
|
||||
if shared.args.cai_chat:
|
||||
return generate_chat_html(shared.history['visible'], name1, name2, shared.character)
|
||||
else:
|
||||
return shared.history['visible']
|
||||
|
||||
return generate_chat_output(shared.history['visible'], name1, name2, shared.character)
|
||||
|
||||
def redraw_html(name1, name2):
|
||||
return generate_chat_html(shared.history['visible'], name1, name2, shared.character)
|
||||
|
|
|
|||
|
|
@ -1,4 +1,3 @@
|
|||
import os
|
||||
import sys
|
||||
from pathlib import Path
|
||||
|
||||
|
|
@ -7,7 +6,7 @@ import torch
|
|||
|
||||
import modules.shared as shared
|
||||
|
||||
sys.path.insert(0, os.path.abspath(Path("repositories/GPTQ-for-LLaMa")))
|
||||
sys.path.insert(0, str(Path("repositories/GPTQ-for-LLaMa")))
|
||||
from llama import load_quant
|
||||
|
||||
|
||||
|
|
@ -41,9 +40,9 @@ def load_quantized_LLaMA(model_name):
|
|||
print(f"Could not find {pt_model}, exiting...")
|
||||
exit()
|
||||
|
||||
model = load_quant(path_to_model, os.path.abspath(pt_path), bits)
|
||||
model = load_quant(str(path_to_model), str(pt_path), bits)
|
||||
|
||||
# Multi-GPU setup
|
||||
# Multiple GPUs or GPU+CPU
|
||||
if shared.args.gpu_memory:
|
||||
max_memory = {}
|
||||
for i in range(len(shared.args.gpu_memory)):
|
||||
|
|
|
|||
|
|
@ -85,12 +85,12 @@ parser.add_argument('--nvme-offload-dir', type=str, help='DeepSpeed: Directory t
|
|||
parser.add_argument('--local_rank', type=int, default=0, help='DeepSpeed: Optional argument for distributed setups.')
|
||||
parser.add_argument('--rwkv-strategy', type=str, default=None, help='RWKV: The strategy to use while loading the model. Examples: "cpu fp32", "cuda fp16", "cuda fp16i8".')
|
||||
parser.add_argument('--rwkv-cuda-on', action='store_true', help='RWKV: Compile the CUDA kernel for better performance.')
|
||||
parser.add_argument('--no-stream', action='store_true', help='Don\'t stream the text output in real time. This improves the text generation performance.')
|
||||
parser.add_argument('--no-stream', action='store_true', help='Don\'t stream the text output in real time.')
|
||||
parser.add_argument('--settings', type=str, help='Load the default interface settings from this json file. See settings-template.json for an example. If you create a file called settings.json, this file will be loaded by default without the need to use the --settings flag.')
|
||||
parser.add_argument('--extensions', type=str, nargs="+", help='The list of extensions to load. If you want to load more than one extension, write the names separated by spaces.')
|
||||
parser.add_argument('--listen', action='store_true', help='Make the web UI reachable from your local network.')
|
||||
parser.add_argument('--listen-port', type=int, help='The listening port that the server will use.')
|
||||
parser.add_argument('--share', action='store_true', help='Create a public URL. This is useful for running the web UI on Google Colab or similar.')
|
||||
parser.add_argument('--auto-launch', action='store_true', default=False, help='Open the web UI in the default browser upon launch.')
|
||||
parser.add_argument('--verbose', action='store_true', help='Print the prompts to the terminal.')
|
||||
parser.add_argument('--auto-launch', action='store_true', default=False, help='Open the web UI in the default browser upon launch')
|
||||
args = parser.parse_args()
|
||||
|
|
|
|||
|
|
@ -37,9 +37,13 @@ def encode(prompt, tokens_to_generate=0, add_special_tokens=True):
|
|||
return input_ids.cuda()
|
||||
|
||||
def decode(output_ids):
|
||||
reply = shared.tokenizer.decode(output_ids, skip_special_tokens=True)
|
||||
reply = reply.replace(r'<|endoftext|>', '')
|
||||
return reply
|
||||
# Open Assistant relies on special tokens like <|endoftext|>
|
||||
if re.match('oasst-*', shared.model_name.lower()):
|
||||
return shared.tokenizer.decode(output_ids, skip_special_tokens=False)
|
||||
else:
|
||||
reply = shared.tokenizer.decode(output_ids, skip_special_tokens=True)
|
||||
reply = reply.replace(r'<|endoftext|>', '')
|
||||
return reply
|
||||
|
||||
def generate_softprompt_input_tensors(input_ids):
|
||||
inputs_embeds = shared.model.transformer.wte(input_ids)
|
||||
|
|
@ -119,7 +123,9 @@ def generate_reply(question, max_new_tokens, do_sample, temperature, top_p, typi
|
|||
original_input_ids = input_ids
|
||||
output = input_ids[0]
|
||||
cuda = "" if (shared.args.cpu or shared.args.deepspeed or shared.args.flexgen) else ".cuda()"
|
||||
n = shared.tokenizer.eos_token_id if eos_token is None else int(encode(eos_token)[0][-1])
|
||||
eos_token_ids = [shared.tokenizer.eos_token_id] if shared.tokenizer.eos_token_id is not None else []
|
||||
if eos_token is not None:
|
||||
eos_token_ids.append(int(encode(eos_token)[0][-1]))
|
||||
stopping_criteria_list = transformers.StoppingCriteriaList()
|
||||
if stopping_string is not None:
|
||||
# Copied from https://github.com/PygmalionAI/gradio-ui/blob/master/src/model.py
|
||||
|
|
@ -129,7 +135,7 @@ def generate_reply(question, max_new_tokens, do_sample, temperature, top_p, typi
|
|||
if not shared.args.flexgen:
|
||||
generate_params = [
|
||||
f"max_new_tokens=max_new_tokens",
|
||||
f"eos_token_id={n}",
|
||||
f"eos_token_id={eos_token_ids}",
|
||||
f"stopping_criteria=stopping_criteria_list",
|
||||
f"do_sample={do_sample}",
|
||||
f"temperature={temperature}",
|
||||
|
|
@ -149,7 +155,7 @@ def generate_reply(question, max_new_tokens, do_sample, temperature, top_p, typi
|
|||
f"max_new_tokens={max_new_tokens if shared.args.no_stream else 8}",
|
||||
f"do_sample={do_sample}",
|
||||
f"temperature={temperature}",
|
||||
f"stop={n}",
|
||||
f"stop={eos_token_ids[-1]}",
|
||||
]
|
||||
if shared.args.deepspeed:
|
||||
generate_params.append("synced_gpus=True")
|
||||
|
|
@ -196,10 +202,12 @@ def generate_reply(question, max_new_tokens, do_sample, temperature, top_p, typi
|
|||
|
||||
if not (shared.args.chat or shared.args.cai_chat):
|
||||
reply = original_question + apply_extensions(reply[len(question):], "output")
|
||||
|
||||
if output[-1] in eos_token_ids:
|
||||
break
|
||||
yield formatted_outputs(reply, shared.model_name)
|
||||
|
||||
if output[-1] == n:
|
||||
break
|
||||
yield formatted_outputs(reply, shared.model_name)
|
||||
|
||||
# Stream the output naively for FlexGen since it doesn't support 'stopping_criteria'
|
||||
else:
|
||||
|
|
@ -213,15 +221,17 @@ def generate_reply(question, max_new_tokens, do_sample, temperature, top_p, typi
|
|||
|
||||
if not (shared.args.chat or shared.args.cai_chat):
|
||||
reply = original_question + apply_extensions(reply[len(question):], "output")
|
||||
yield formatted_outputs(reply, shared.model_name)
|
||||
|
||||
if np.count_nonzero(input_ids[0] == n) < np.count_nonzero(output == n):
|
||||
if np.count_nonzero(np.isin(input_ids[0], eos_token_ids)) < np.count_nonzero(np.isin(output, eos_token_ids)):
|
||||
break
|
||||
yield formatted_outputs(reply, shared.model_name)
|
||||
|
||||
input_ids = np.reshape(output, (1, output.shape[0]))
|
||||
if shared.soft_prompt:
|
||||
inputs_embeds, filler_input_ids = generate_softprompt_input_tensors(input_ids)
|
||||
|
||||
yield formatted_outputs(reply, shared.model_name)
|
||||
|
||||
finally:
|
||||
t1 = time.time()
|
||||
print(f"Output generated in {(t1-t0):.2f} seconds ({(len(output)-len(original_input_ids[0]))/(t1-t0):.2f} tokens/s, {len(output)-len(original_input_ids[0])} tokens)")
|
||||
|
|
|
|||
|
|
@ -1,12 +1,12 @@
|
|||
accelerate==0.16.0
|
||||
accelerate==0.17.0
|
||||
bitsandbytes==0.37.0
|
||||
flexgen==0.1.7
|
||||
gradio==3.18.0
|
||||
numpy
|
||||
requests
|
||||
rwkv==0.1.0
|
||||
safetensors==0.2.8
|
||||
rwkv==0.3.1
|
||||
safetensors==0.3.0
|
||||
sentencepiece
|
||||
tqdm
|
||||
markdown
|
||||
git+https://github.com/zphang/transformers@llama_push
|
||||
git+https://github.com/zphang/transformers.git@68d640f7c368bcaaaecfc678f11908ebbd3d6176
|
||||
|
|
@ -269,10 +269,10 @@ if shared.args.chat or shared.args.cai_chat:
|
|||
|
||||
function_call = 'chat.cai_chatbot_wrapper' if shared.args.cai_chat else 'chat.chatbot_wrapper'
|
||||
|
||||
gen_events.append(shared.gradio['Generate'].click(eval(function_call), shared.input_params, shared.gradio['display'], show_progress=False, api_name='textgen'))
|
||||
gen_events.append(shared.gradio['textbox'].submit(eval(function_call), shared.input_params, shared.gradio['display'], show_progress=False))
|
||||
gen_events.append(shared.gradio['Regenerate'].click(chat.regenerate_wrapper, shared.input_params, shared.gradio['display'], show_progress=False))
|
||||
gen_events.append(shared.gradio['Impersonate'].click(chat.impersonate_wrapper, shared.input_params, shared.gradio['textbox'], show_progress=False))
|
||||
gen_events.append(shared.gradio['Generate'].click(eval(function_call), shared.input_params, shared.gradio['display'], show_progress=shared.args.no_stream, api_name='textgen'))
|
||||
gen_events.append(shared.gradio['textbox'].submit(eval(function_call), shared.input_params, shared.gradio['display'], show_progress=shared.args.no_stream))
|
||||
gen_events.append(shared.gradio['Regenerate'].click(chat.regenerate_wrapper, shared.input_params, shared.gradio['display'], show_progress=shared.args.no_stream))
|
||||
gen_events.append(shared.gradio['Impersonate'].click(chat.impersonate_wrapper, shared.input_params, shared.gradio['textbox'], show_progress=shared.args.no_stream))
|
||||
shared.gradio['Stop'].click(chat.stop_everything_event, [], [], cancels=gen_events)
|
||||
|
||||
shared.gradio['Copy last reply'].click(chat.send_last_reply_to_input, [], shared.gradio['textbox'], show_progress=shared.args.no_stream)
|
||||
|
|
|
|||
Loading…
Reference in a new issue