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'use client' import { useState, useEffect, useRef, useCallback } from 'react' export default function Home() { // Keep track of the classification result and the model loading status. const [result, setResult] = useState(null); const [ready, setReady] = useState(null); // Create a reference to the worker ob...
transformers.js/examples/next-client/src/app/page.js/0
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import { useEffect, useRef, useState } from 'react' import LanguageSelector from './components/LanguageSelector'; import Progress from './components/Progress'; import './App.css' function App() { // Model loading const [ready, setReady] = useState(null); const [disabled, setDisabled] = useState(false); const...
transformers.js/examples/react-translator/src/App.jsx/0
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<!DOCTYPE html> <html lang="en"> <head> <meta charset="UTF-8" /> <link rel="stylesheet" href="index.css" /> <meta name="viewport" content="width=device-width, initial-scale=1.0" /> <title>Transformers.js - Segment Anything WebGPU</title> </head> <body> <h1>Segment Anything WebGPU</h1> <h3>In-...
transformers.js/examples/segment-anything-client/index.html/0
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import { downloadImage } from '../utils.js' import Image from 'next/image' export function Modal({ currentImage, setCurrentImage }) { return ( <div className='fixed inset-0 z-30 backdrop-blur-2xl w-full h-full bg-black top-0 left-0 transition' style={{ backgroundColo...
transformers.js/examples/semantic-image-search/src/app/components/Modal.jsx/0
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import { useEffect, useRef } from "react"; export default function AudioPlayer({ audioUrl, mimeType }) { const audioPlayer = useRef(null); const audioSource = useRef(null); // Updates src when url changes useEffect(() => { if (audioPlayer.current && audioSource.current) { audioSour...
transformers.js/examples/text-to-speech-client/src/components/AudioPlayer.jsx/0
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#root { max-width: 1280px; width: 100%; margin: 0 auto; padding: 2rem; text-align: center; display: flex; justify-content: center; align-items: center; flex-direction: column; }
transformers.js/examples/tokenizer-playground/src/App.css/0
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export default function UserIcon(props) { return ( <svg {...props} xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" strokeWidth="2" strok...
transformers.js/examples/webgpu-vlm/src/components/icons/UserIcon.jsx/0
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def generate_tokenizer_json(tokenizer): vocab = tokenizer.vocab special_tokens_vocab = vocab if "<pad>" not in tokenizer.vocab: # For MMS tokenizers, the vocab is of the form: # { # language_id: { language_vocab } # } # So, to get the list of special tokens, we ju...
transformers.js/scripts/extra/wav2vec2.py/0
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/** * @file Definitions of all models available in Transformers.js. * * **Example:** Load and run an `AutoModel`. * * ```javascript * import { AutoModel, AutoTokenizer } from '@huggingface/transformers'; * * let tokenizer = await AutoTokenizer.from_pretrained('Xenova/bert-base-uncased'); * let model = awai...
transformers.js/src/models.js/0
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export * from './audio_spectrogram_transformer/feature_extraction_audio_spectrogram_transformer.js'; export * from './clap/feature_extraction_clap.js'; export * from './moonshine/feature_extraction_moonshine.js'; export * from './pyannote/feature_extraction_pyannote.js'; export * from './seamless_m4t/feature_extractio...
transformers.js/src/models/feature_extractors.js/0
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import { FeatureExtractor, validate_audio_inputs } from '../../base/feature_extraction_utils.js'; import { Tensor } from '../../utils/tensor.js'; import { max, softmax } from '../../utils/maths.js'; export class PyAnnoteFeatureExtractor extends FeatureExtractor { /** * Asynchronously extracts features from a...
transformers.js/src/models/pyannote/feature_extraction_pyannote.js/0
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import { ImageProcessor, } from "../../base/image_processors_utils.js"; export class VitPoseImageProcessor extends ImageProcessor { /** * Transform the heatmaps into keypoint predictions and transform them back to the image. * NOTE: This is a naive implementation and does not include advanced post-p...
transformers.js/src/models/vitpose/image_processing_vitpose.js/0
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/** * @file Core utility functions/classes for Transformers.js. * * These are only used internally, meaning an end-user shouldn't * need to access anything here. * * @module utils/core */ /** * @typedef {Object} InitiateProgressInfo * @property {'initiate'} status * @property {string} name The model id or d...
transformers.js/src/utils/core.js/0
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import { GPT2Tokenizer, GPT2LMHeadModel } from "../../../src/transformers.js"; import { MAX_MODEL_LOAD_TIME, MAX_TEST_EXECUTION_TIME, MAX_MODEL_DISPOSE_TIME, DEFAULT_MODEL_OPTIONS } from "../../init.js"; export default () => { describe("GPT2LMHeadModel", () => { const model_id = "hf-internal-testing/tiny-random...
transformers.js/tests/models/gpt2/test_modeling_gpt2.js/0
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import { LlamaTokenizer, LlamaForCausalLM } from "../../../src/transformers.js"; import { MAX_MODEL_LOAD_TIME, MAX_TEST_EXECUTION_TIME, MAX_MODEL_DISPOSE_TIME, MAX_TEST_TIME, DEFAULT_MODEL_OPTIONS } from "../../init.js"; export default () => { describe("LlamaForCausalLM", () => { const model_id = "hf-internal-t...
transformers.js/tests/models/llama/test_modeling_llama.js/0
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import { AutoImageProcessor, SamImageProcessor } from "../../../src/transformers.js"; import { load_cached_image } from "../../asset_cache.js"; import { MAX_PROCESSOR_LOAD_TIME, MAX_TEST_EXECUTION_TIME } from "../../init.js"; export default () => { // SamImageProcessor // - tests normal padding (do_pad=true, pad...
transformers.js/tests/models/sam/test_image_processing_sam.js/0
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import { WhisperTokenizer } from "../../../src/tokenizers.js"; import { BASE_TEST_STRINGS, WHISPER_TEST_STRINGS } from "../test_strings.js"; import { compare } from "../../test_utils.js"; export const TOKENIZER_CLASS = WhisperTokenizer; export const TEST_CONFIG = { "onnx-community/whisper-tiny.en": { SIMPLE: { ...
transformers.js/tests/models/whisper/test_tokenization_whisper.js/0
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import { pipeline, QuestionAnsweringPipeline } from "../../src/transformers.js"; import { MAX_MODEL_LOAD_TIME, MAX_TEST_EXECUTION_TIME, MAX_MODEL_DISPOSE_TIME, DEFAULT_MODEL_OPTIONS } from "../init.js"; const PIPELINE_ID = "question-answering"; export default () => { describe("Question Answering", () => { cons...
transformers.js/tests/pipelines/test_pipelines_question_answering.js/0
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import { // Models AutoModelForSeq2SeqLM, AutoModelForCausalLM, LlamaForCausalLM, LlavaForConditionalGeneration, // Tokenizers AutoTokenizer, LlamaTokenizer, // Processors AutoProcessor, Processor, // Other TextStreamer, RawImage, } from "../../src/transformers.js"; import { init, MAX_TE...
transformers.js/tests/utils/generation.test.js/0
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FROM nvidia/cuda:10.2-cudnn7-devel-ubuntu18.04 LABEL maintainer="Hugging Face" LABEL repository="transformers" RUN apt update && \ apt install -y bash \ build-essential \ git \ curl \ ca-certificates \ python3 \ ...
transformers/docker/transformers-gpu/Dockerfile/0
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# المعالجة المسبقة Preprocessing [[open-in-colab]] قبل تدريب نموذج على مجموعة بيانات، يجب معالجتها مسبقًا وفقًا تنسيق المتوقع لمدخلات النموذج. سواء كانت بياناتك نصية أو صورًا أو صوتًا، فيجب تحويلها وتجميعها في دفعات من الموترات. يوفر 🤗 Transformers مجموعة من فئات المعالجة المسبقة للمساعدة في إعداد بياناتك للنموذج. ...
transformers/docs/source/ar/preprocessing.md/0
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# Tiktoken والتفاعل مع Transformers يتم دمج دعم ملفات نموذج tiktoken بسلاسة في 🤗 transformers عند تحميل النماذج `from_pretrained` مع ملف `tokenizer.model` tiktoken على Hub، والذي يتم تحويله تلقائيًا إلى [المحلل اللغوي السريع](https://huggingface.co/docs/transformers/main/en/main_classes/tokenizer#transformers.PreTrai...
transformers/docs/source/ar/tiktoken.md/0
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<!--Copyright 2022 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/de/model_sharing.md/0
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transformers/docs/source/en/agents.md/0
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<!--Copyright 2023 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/en/generation_strategies.md/0
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<!--Copyright 2024 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/en/kv_cache.md/0
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transformers/docs/source/en/main_classes/onnx.md/0
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<!--Copyright 2024 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/en/model_doc/bamba.md/0
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transformers/docs/source/en/model_doc/deberta-v2.md/0
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transformers/docs/source/en/model_doc/dit.md/0
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transformers/docs/source/en/model_doc/gpt-sw3.md/0
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transformers/docs/source/en/model_doc/layoutlmv2.md/0
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transformers/docs/source/en/model_doc/lxmert.md/0
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transformers/docs/source/en/model_doc/rag.md/0
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transformers/docs/source/en/model_doc/superpoint.md/0
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transformers/docs/source/en/model_doc/transfo-xl.md/0
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transformers/docs/source/en/model_doc/vision-encoder-decoder.md/0
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transformers/docs/source/en/model_doc/wavlm.md/0
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transformers/docs/source/en/model_doc/zamba2.md/0
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<!--Copyright 2022 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/en/perf_train_cpu_many.md/0
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transformers/docs/source/en/quantization/compressed_tensors.md/0
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transformers/docs/source/en/task_summary.md/0
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transformers/docs/source/en/tasks/multiple_choice.md/0
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transformers/docs/source/en/testing.md/0
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transformers/docs/source/es/chat_templating.md/0
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<!--⚠️ Note that this file is in Markdown but contain specific syntax for our doc-builder (similar to MDX) that may not be rendered properly in your Markdown viewer. --> # Pipelines pour l'inférence L'objet [`pipeline`] rend simple l'utilisation de n'importe quel modèle du [Hub](https://huggingface.co/models) pour l'...
transformers/docs/source/fr/tutoriel_pipeline.md/0
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transformers/docs/source/it/debugging.md/0
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<!--- Copyright 2020 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or ...
transformers/docs/source/it/pr_checks.md/0
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transformers/docs/source/ja/custom_models.md/0
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transformers/docs/source/ja/main_classes/processors.md/0
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transformers/docs/source/ja/model_doc/bert-generation.md/0
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transformers/docs/source/ja/model_doc/byt5.md/0
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transformers/docs/source/ja/model_doc/ctrl.md/0
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transformers/docs/source/ja/multilingual.md/0
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<!--- Copyright 2021 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or ...
transformers/docs/source/ja/performance.md/0
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transformers/docs/source/ja/tasks/image_classification.md/0
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transformers/docs/source/ja/tasks/video_classification.md/0
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transformers/docs/source/ko/add_new_model.md/0
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transformers/docs/source/ko/generation_strategies.md/0
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<!--Copyright 2023 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/ko/llm_tutorial.md/0
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# AltCLIP ## 개요[[overview]] AltCLIP 모델은 Zhongzhi Chen, Guang Liu, Bo-Wen Zhang, Fulong Ye, Qinghong Yang, Ledell Wu의 [AltCLIP: Altering the Language Encoder in CLIP for Extended Language Capabilities](https://arxiv.org/abs/2211.06679v2) 논문에서 제안되었습니다. AltCLIP(CLIP의 언어 인코더를 변경하여 언어 기능 확장)은 다양한 이미지-텍스트 및 텍스트-텍스트 쌍으로 훈련된...
transformers/docs/source/ko/model_doc/altclip.md/0
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transformers/docs/source/ko/model_doc/dbrx.md/0
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<!--Copyright 2023 Mistral AI and The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicabl...
transformers/docs/source/ko/model_doc/mistral.md/0
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<!--Copyright 2022 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/ko/model_sharing.md/0
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transformers/docs/source/ko/philosophy.md/0
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<!--Copyright 2022 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/ko/tasks/audio_classification.md/0
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<!--Copyright 2022 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/ko/tasks/semantic_segmentation.md/0
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transformers/docs/source/pt/quicktour.md/0
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transformers/docs/source/zh/attention.md/0
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<!--- Copyright 2022 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or ...
transformers/docs/source/zh/perf_hardware.md/0
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<!--Copyright 2024 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/zh/tiktoken.md/0
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#!/usr/bin/env python # coding=utf-8 # Copyright 2021 The HuggingFace Team All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-...
transformers/examples/flax/language-modeling/run_mlm_flax.py/0
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#!/usr/bin/env python # coding=utf-8 # Copyright 2021 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LI...
transformers/examples/flax/text-classification/run_flax_glue.py/0
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import argparse import glob import logging import os import time from argparse import Namespace import numpy as np import torch from lightning_base import BaseTransformer, add_generic_args, generic_train from torch.utils.data import DataLoader, TensorDataset from transformers import glue_compute_metrics as compute_me...
transformers/examples/legacy/pytorch-lightning/run_glue.py/0
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#!/usr/bin/env python # Copyright 2020 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless...
transformers/examples/legacy/seq2seq/convert_model_to_fp16.py/0
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#!/usr/bin/env python # Copyright 2020 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless...
transformers/examples/legacy/seq2seq/run_distributed_eval.py/0
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# Note that llama and cohere have different definitions for rotate_half from transformers.models.cohere.modeling_cohere import rotate_half # noqa from transformers.models.llama.modeling_llama import LlamaAttention # When following LlamaAttention dependencies, we will grab the function `rotate_half` defined # in `mod...
transformers/examples/modular-transformers/modular_switch_function.py/0
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#!/usr/bin/env python # coding=utf-8 # Copyright 2022 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LI...
transformers/examples/pytorch/image-pretraining/run_mae.py/0
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<!--- Copyright 2020 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or ...
transformers/examples/pytorch/multiple-choice/README.md/0
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#!/usr/bin/env python # coding=utf-8 # Copyright 2021 The HuggingFace Team All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-...
transformers/examples/pytorch/question-answering/run_seq2seq_qa.py/0
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<!--- Copyright 2020 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or ...
transformers/examples/pytorch/summarization/README.md/0
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<!--- Copyright 2020 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or ...
transformers/examples/pytorch/token-classification/README.md/0
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# Patience-based Early Exit Patience-based Early Exit (PABEE) is a plug-and-play inference method for pretrained language models. We have already implemented it on BERT and ALBERT. Basically, you can make your LM faster and more robust with PABEE. It can even improve the performance of ALBERT on GLUE. The only sacrifi...
transformers/examples/research_projects/bert-loses-patience/README.md/0
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# coding=utf-8 # Copyright 2019-present, the HuggingFace Inc. team and Facebook, Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Un...
transformers/examples/research_projects/distillation/distiller.py/0
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<p align="center"> <img src="http://sayef.tech:8082/uploads/FSNER-LOGO-2.png" alt="FSNER LOGO"> </p> <p align="center"> Implemented by <a href="https://huggingface.co/sayef"> sayef </a>. </p> ## Overview The FSNER model was proposed in [Example-Based Named Entity Recognition](https://arxiv.org/abs/2008.10570) by ...
transformers/examples/research_projects/fsner/README.md/0
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import json import os from dataclasses import dataclass from functools import partial from typing import Callable import flax.linen as nn import jax import jax.numpy as jnp import joblib import optax import wandb from flax import jax_utils, struct, traverse_util from flax.serialization import from_bytes, to_bytes from...
transformers/examples/research_projects/jax-projects/big_bird/bigbird_flax.py/0
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# Wav2Vec2 Contrastive Loss PreTraining examples The following example showcases how to pretrain a wav2vec2 model using the JAX/Flax backend. Pretraining Wav2Vec2 is rather complex, so it is highly recommended to read the [official paper](https://arxiv.org/abs/2006.11477). JAX/Flax allows you to trace pure functions...
transformers/examples/research_projects/jax-projects/wav2vec2/README.md/0
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# coding=utf-8 # Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team. # Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a cop...
transformers/examples/research_projects/movement-pruning/emmental/configuration_bert_masked.py/0
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# coding=utf-8 # Copyright 2020 The Google Research Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicab...
transformers/examples/research_projects/performer/modeling_flax_performer_utils.py/0
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# coding=utf-8 # Copyright 2020 The HuggingFace Team All rights reserved. # Copyright 2021 NVIDIA Corporation. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # htt...
transformers/examples/research_projects/quantization-qdqbert/trainer_quant_qa.py/0
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# coding=utf-8 # Copyright 2022 The Google Research Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicab...
transformers/examples/research_projects/self-training-text-classification/selftraining.py/0
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# Add parent directory to python path to access lightning_base.py export PYTHONPATH="../":"${PYTHONPATH}" python finetune.py \ --data_dir=$CNN_DIR \ --learning_rate=3e-5 \ --train_batch_size=$BS \ --eval_batch_size=$BS \ --output_dir=$OUTPUT_DIR \ --max_source_length=512 \ --max_target_length=56 \ --val_check_interval...
transformers/examples/research_projects/seq2seq-distillation/finetune_t5.sh/0
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import os from glob import glob import imageio import torch import torchvision import wandb from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan from loaders import load_vqgan from PIL import Image from torch import nn from transformers import CLIPModel, CLIPTokenizerFast from uti...
transformers/examples/research_projects/vqgan-clip/VQGAN_CLIP.py/0
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#!/usr/bin/env python # coding=utf-8 # Copyright The HuggingFace Team and The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.ap...
transformers/examples/tensorflow/multiple-choice/run_swag.py/0
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<!--- Copyright 2021 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or ...
transformers/examples/tensorflow/translation/README.md/0
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#!/usr/bin/env python # coding: utf-8 # Copyright 2020 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENS...
transformers/scripts/fsmt/fsmt-make-tiny-model.py/0
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#!/usr/bin/env python # coding=utf-8 # Copyright 2024 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/L...
transformers/src/transformers/agents/agents.py/0
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# coding=utf-8 # Copyright 2018 The HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable...
transformers/src/transformers/convert_slow_tokenizer.py/0
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# Copyright 2020 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
transformers/src/transformers/debug_utils.py/0
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# coding=utf-8 # Copyright 2023 The HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable...
transformers/src/transformers/generation/streamers.py/0
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