mirror of
https://github.com/oobabooga/text-generation-webui.git
synced 2024-12-27 06:39:33 +01:00
commit
a4b732c30b
@ -135,6 +135,7 @@ def convert_history(history):
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current_message = ""
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current_reply = ""
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user_input = ""
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user_input_last = True
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system_message = ""
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# Multimodal: convert OpenAI format to multimodal extension format
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@ -188,6 +189,7 @@ def convert_history(history):
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if role == "user":
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user_input = content
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user_input_last = True
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if current_message:
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chat_dialogue.append([current_message, ''])
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current_message = ""
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@ -195,6 +197,7 @@ def convert_history(history):
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current_message = content
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elif role == "assistant":
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current_reply = content
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user_input_last = False
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if current_message:
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chat_dialogue.append([current_message, current_reply])
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current_message = ""
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@ -204,13 +207,13 @@ def convert_history(history):
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elif role == "system":
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system_message = content
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# if current_message:
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# chat_dialogue.append([current_message, ''])
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if not user_input_last:
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user_input = ""
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return user_input, system_message, {'internal': chat_dialogue, 'visible': copy.deepcopy(chat_dialogue)}
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def chat_completions_common(body: dict, is_legacy: bool = False, stream=False) -> dict:
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def chat_completions_common(body: dict, is_legacy: bool = False, stream=False, prompt_only=False) -> dict:
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if body.get('functions', []):
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raise InvalidRequestError(message="functions is not supported.", param='functions')
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@ -310,14 +313,18 @@ def chat_completions_common(body: dict, is_legacy: bool = False, stream=False) -
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# chunk[resp_list][0]["logprobs"] = None
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return chunk
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if stream:
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yield chat_streaming_chunk('')
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# generate reply #######################################
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prompt = generate_chat_prompt(user_input, generate_params)
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prompt = generate_chat_prompt(user_input, generate_params, _continue=continue_)
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if prompt_only:
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yield {'prompt': prompt}
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return
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token_count = len(encode(prompt)[0])
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debug_msg({'prompt': prompt, 'generate_params': generate_params})
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if stream:
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yield chat_streaming_chunk('')
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generator = generate_chat_reply(
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user_input, generate_params, regenerate=False, _continue=continue_, loading_message=False)
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@ -9,7 +9,8 @@ from modules.utils import get_available_loras, get_available_models
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def get_current_model_info():
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return {
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'model_name': shared.model_name,
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'lora_names': shared.lora_names
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'lora_names': shared.lora_names,
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'loader': shared.args.loader
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}
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@ -3,6 +3,7 @@ import json
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import logging
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import os
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import traceback
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from collections import deque
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from threading import Thread
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import speech_recognition as sr
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@ -31,6 +32,7 @@ from modules.text_generation import stop_everything_event
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from .typing import (
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ChatCompletionRequest,
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ChatCompletionResponse,
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ChatPromptResponse,
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CompletionRequest,
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CompletionResponse,
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DecodeRequest,
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@ -259,6 +261,15 @@ async def handle_logits(request_data: LogitsRequest):
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return JSONResponse(response)
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@app.post('/v1/internal/chat-prompt', response_model=ChatPromptResponse, dependencies=check_key)
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async def handle_chat_prompt(request: Request, request_data: ChatCompletionRequest):
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path = request.url.path
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is_legacy = "/generate" in path
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generator = OAIcompletions.chat_completions_common(to_dict(request_data), is_legacy=is_legacy, prompt_only=True)
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response = deque(generator, maxlen=1).pop()
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return JSONResponse(response)
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@app.post("/v1/internal/stop-generation", dependencies=check_key)
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async def handle_stop_generation(request: Request):
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stop_everything_event()
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@ -124,6 +124,10 @@ class ChatCompletionResponse(BaseModel):
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usage: dict
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class ChatPromptResponse(BaseModel):
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prompt: str
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class EmbeddingsRequest(BaseModel):
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input: str | List[str] | List[int] | List[List[int]]
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model: str | None = Field(default=None, description="Unused parameter. To change the model, set the OPENEDAI_EMBEDDING_MODEL and OPENEDAI_EMBEDDING_DEVICE environment variables before starting the server.")
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@ -62,7 +62,7 @@ def ui():
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whipser_model = gr.Dropdown(label='Whisper Model', value=params['whipser_model'], choices=["tiny.en", "base.en", "small.en", "medium.en", "tiny", "base", "small", "medium", "large"])
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whipser_language = gr.Dropdown(label='Whisper Language', value=params['whipser_language'], choices=["chinese", "german", "spanish", "russian", "korean", "french", "japanese", "portuguese", "turkish", "polish", "catalan", "dutch", "arabic", "swedish", "italian", "indonesian", "hindi", "finnish", "vietnamese", "hebrew", "ukrainian", "greek", "malay", "czech", "romanian", "danish", "hungarian", "tamil", "norwegian", "thai", "urdu", "croatian", "bulgarian", "lithuanian", "latin", "maori", "malayalam", "welsh", "slovak", "telugu", "persian", "latvian", "bengali", "serbian", "azerbaijani", "slovenian", "kannada", "estonian", "macedonian", "breton", "basque", "icelandic", "armenian", "nepali", "mongolian", "bosnian", "kazakh", "albanian", "swahili", "galician", "marathi", "punjabi", "sinhala", "khmer", "shona", "yoruba", "somali", "afrikaans", "occitan", "georgian", "belarusian", "tajik", "sindhi", "gujarati", "amharic", "yiddish", "lao", "uzbek", "faroese", "haitian creole", "pashto", "turkmen", "nynorsk", "maltese", "sanskrit", "luxembourgish", "myanmar", "tibetan", "tagalog", "malagasy", "assamese", "tatar", "hawaiian", "lingala", "hausa", "bashkir", "javanese", "sundanese"])
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audio.change(
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audio.stop_recording(
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auto_transcribe, [audio, auto_submit, whipser_model, whipser_language], [shared.gradio['textbox'], audio]).then(
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None, auto_submit, None, js="(check) => {if (check) { document.getElementById('Generate').click() }}")
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@ -136,9 +136,6 @@ def get_model_metadata(model):
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if 'instruction_template' not in model_settings:
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model_settings['instruction_template'] = 'Alpaca'
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if model_settings['instruction_template'] != 'Custom (obtained from model metadata)':
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model_settings['instruction_template_str'] = chat.load_instruction_template(model_settings['instruction_template'])
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# Ignore rope_freq_base if set to the default value
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if 'rope_freq_base' in model_settings and model_settings['rope_freq_base'] == 10000:
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model_settings.pop('rope_freq_base')
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@ -150,6 +147,10 @@ def get_model_metadata(model):
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for k in settings[pat]:
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model_settings[k] = settings[pat][k]
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# Load instruction template if defined by name rather than by value
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if model_settings['instruction_template'] != 'Custom (obtained from model metadata)':
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model_settings['instruction_template_str'] = chat.load_instruction_template(model_settings['instruction_template'])
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return model_settings
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@ -23,14 +23,14 @@ safetensors==0.4.*
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scipy
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sentencepiece
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tensorboard
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transformers==4.39.*
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transformers==4.40.*
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tqdm
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wandb
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# API
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SpeechRecognition==3.10.0
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flask_cloudflared==0.0.14
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sse-starlette==2.1.0
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sse-starlette==1.6.5
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tiktoken
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# llama-cpp-python (CPU only, AVX2)
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@ -21,14 +21,14 @@ safetensors==0.4.*
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scipy
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sentencepiece
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tensorboard
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transformers==4.39.*
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transformers==4.40.*
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tqdm
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wandb
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# API
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SpeechRecognition==3.10.0
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flask_cloudflared==0.0.14
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sse-starlette==2.1.0
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sse-starlette==1.6.5
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tiktoken
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# llama-cpp-python (CPU only, AVX2)
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@ -21,14 +21,14 @@ safetensors==0.4.*
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scipy
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sentencepiece
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tensorboard
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transformers==4.39.*
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transformers==4.40.*
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tqdm
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wandb
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# API
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SpeechRecognition==3.10.0
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flask_cloudflared==0.0.14
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sse-starlette==2.1.0
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sse-starlette==1.6.5
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tiktoken
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# llama-cpp-python (CPU only, no AVX2)
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@ -21,14 +21,14 @@ safetensors==0.4.*
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scipy
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sentencepiece
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tensorboard
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transformers==4.39.*
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transformers==4.40.*
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tqdm
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wandb
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# API
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SpeechRecognition==3.10.0
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flask_cloudflared==0.0.14
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sse-starlette==2.1.0
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sse-starlette==1.6.5
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tiktoken
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# Mac wheels
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@ -21,14 +21,14 @@ safetensors==0.4.*
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scipy
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sentencepiece
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tensorboard
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transformers==4.39.*
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transformers==4.40.*
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tqdm
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wandb
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# API
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SpeechRecognition==3.10.0
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flask_cloudflared==0.0.14
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sse-starlette==2.1.0
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sse-starlette==1.6.5
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tiktoken
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# Mac wheels
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@ -21,14 +21,14 @@ safetensors==0.4.*
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scipy
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sentencepiece
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tensorboard
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transformers==4.39.*
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transformers==4.40.*
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tqdm
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wandb
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# API
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SpeechRecognition==3.10.0
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flask_cloudflared==0.0.14
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sse-starlette==2.1.0
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sse-starlette==1.6.5
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tiktoken
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# llama-cpp-python (CPU only, AVX2)
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@ -21,14 +21,14 @@ safetensors==0.4.*
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scipy
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sentencepiece
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tensorboard
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transformers==4.39.*
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transformers==4.40.*
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tqdm
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wandb
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# API
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SpeechRecognition==3.10.0
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flask_cloudflared==0.0.14
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sse-starlette==2.1.0
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sse-starlette==1.6.5
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tiktoken
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# llama-cpp-python (CPU only, no AVX2)
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@ -23,14 +23,14 @@ safetensors==0.4.*
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scipy
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sentencepiece
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tensorboard
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transformers==4.39.*
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transformers==4.40.*
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tqdm
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wandb
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# API
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SpeechRecognition==3.10.0
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flask_cloudflared==0.0.14
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sse-starlette==2.1.0
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sse-starlette==1.6.5
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tiktoken
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# llama-cpp-python (CPU only, no AVX2)
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@ -21,12 +21,12 @@ safetensors==0.4.*
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scipy
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sentencepiece
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tensorboard
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transformers==4.39.*
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transformers==4.40.*
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tqdm
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wandb
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# API
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SpeechRecognition==3.10.0
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flask_cloudflared==0.0.14
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sse-starlette==2.1.0
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sse-starlette==1.6.5
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tiktoken
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