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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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# Security Policy ## Hugging Face Hub, remote artefacts, and remote code Transformers is open-source software that is tightly coupled to the Hugging Face Hub. While you have the ability to use it offline with pre-downloaded model weights, it provides a very simple way to download, use, and manage models locally. Whe...
transformers/SECURITY.md/0
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FROM python:3.9-slim ENV PYTHONDONTWRITEBYTECODE=1 USER root ARG REF=main RUN apt-get update && apt-get install -y time git g++ pkg-config make git-lfs ENV UV_PYTHON=/usr/local/bin/python RUN pip install uv && uv venv && uv pip install --no-cache-dir -U pip setuptools GitPython RUN pip install --no-cache-dir --upgrade ...
transformers/docker/consistency.dockerfile/0
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ARG BASE_DOCKER_IMAGE FROM $BASE_DOCKER_IMAGE LABEL maintainer="Hugging Face" ARG DEBIAN_FRONTEND=noninteractive # Use login shell to read variables from `~/.profile` (to pass dynamic created variables between RUN commands) SHELL ["sh", "-lc"] RUN apt update RUN apt install -y git libsndfile1-dev tesseract-ocr espea...
transformers/docker/transformers-past-gpu/Dockerfile/0
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- sections: - local: index title: 🤗 المحولات - local: quicktour title: جولة سريعة - local: installation title: التثبيت title: البدء - sections: - local: pipeline_tutorial title: تشغيل الاستنتاج باستخدام خطوط الأنابيب - local: autoclass_tutorial title: كتابة تعليمات برمجية متكيفه باستخدا...
transformers/docs/source/ar/_toctree.yml/0
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# التثبيت (Installation) قم بتثبيت مكتبة 🤗 Transformers المناسبة لمكتبة التعلم العميق التي تستخدمها، وقم بإعداد ذاكرة التخزين المؤقت الخاصة بك، وقم بإعداد 🤗 Transformers للعمل دون اتصال بالإنترنت (اختياري). تم اختبار 🤗 Transformers على Python 3.6 والإصدارات الأحدث، وPyTorch 1.1.0 والإصدارات الأحدث، وTensorFlow 2....
transformers/docs/source/ar/installation.md/0
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# جولة سريعة [[open-in-colab]] ابدأ رحلتك مع مكتبة 🤗 Transformers! سواء كنت مطورًا أو مستخدمًا عاديًا، ستساعدك هذه الجولة السريعة على البدء وستُظهر لك كيفية استخدام [`pipeline`] للاستنتاج، وتحميل نموذج مُدرب مسبقًا ومعالج مُسبق مع [AutoClass](./model_doc/auto)، وتدريب نموذج بسرعة باستخدام PyTorch أو TensorFlow. إذا ...
transformers/docs/source/ar/quicktour.md/0
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# ملخص عن المجزئات اللغوية [[open-in-colab]] في هذه الصفحة، سنتناول بالتفصيل عملية التجزئة. <Youtube id="VFp38yj8h3A"/> كما رأينا في [برنامج تعليمي حول المعالجة المسبقة](preprocessing)، فإن تجزئة النص يقسمه إلى كلمات أو الرموز الفرعية (كلمات جزئية)، والتي يتم بعد ذلك تحويلها إلى معرفات من خلال قائمة بحث. يعد تحويل ...
transformers/docs/source/ar/tokenizer_summary.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 to...
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transformers/docs/source/en/fast_tokenizers.md/0
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transformers/docs/source/en/model_doc/auto.md/0
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transformers/docs/source/en/model_doc/clvp.md/0
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transformers/docs/source/en/model_doc/data2vec.md/0
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transformers/docs/source/en/model_doc/falcon.md/0
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<!--Copyright 2024 The GLM & ZhipuAI team 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 ...
transformers/docs/source/en/model_doc/glm.md/0
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<!--Copyright 2024 JetMoe team 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 applicab...
transformers/docs/source/en/model_doc/jetmoe.md/0
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transformers/docs/source/en/model_doc/llava_onevision.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...
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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 agreed...
transformers/docs/source/en/model_doc/perceiver.md/0
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<!--Copyright 2025 The Qwen 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.apache.org/licenses/LICENSE-2.0 Unless required by a...
transformers/docs/source/en/model_doc/qwen2_5_vl.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/model_doc/tapex.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/model_doc/upernet.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 agreed...
transformers/docs/source/en/model_doc/xls_r.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/en/perf_hardware.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/en/pr_checks.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/quantization/quanto.md/0
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transformers/docs/source/en/tasks/image_text_to_text.md/0
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transformers/docs/source/en/tasks/token_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 ...
transformers/docs/source/en/troubleshooting.md/0
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transformers/docs/source/es/serialization.md/0
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transformers/docs/source/fr/autoclass_tutorial.md/0
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transformers/docs/source/it/add_new_model.md/0
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transformers/docs/source/it/perf_infer_gpu_many.md/0
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transformers/docs/source/ja/add_new_model.md/0
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transformers/docs/source/ja/model_doc/audio-spectrogram-transformer.md/0
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transformers/docs/source/ja/model_doc/deplot.md/0
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transformers/docs/source/ja/run_scripts.md/0
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transformers/docs/source/ja/tokenizer_summary.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/ko/contributing.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 agreed...
transformers/docs/source/ko/model_doc/bertweet.md/0
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<!--Copyright 2022 The HuggingFace Team and Microsoft. All rights reserved. Licensed under the MIT License; you may not use this file except in compliance with the License. Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WAR...
transformers/docs/source/ko/model_doc/graphormer.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_doc/swinv2.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/perf_infer_gpu_one.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/ko/quantization/gptq.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/tasks/language_modeling.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/tasks/zero_shot_object_detection.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 agreed...
transformers/docs/source/pt/converting_tensorflow_models.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/te/quicktour.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 agreed...
transformers/docs/source/zh/custom_models.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 agreed...
transformers/docs/source/zh/main_classes/processors.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/zh/preprocessing.md/0
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# Image Captioning (vision-encoder-text-decoder model) training example The following example showcases how to finetune a vision-encoder-text-decoder model for image captioning using the JAX/Flax backend, leveraging 🤗 Transformers library's [FlaxVisionEncoderDecoderModel](https://huggingface.co/docs/transformers/mode...
transformers/examples/flax/image-captioning/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/legacy/benchmarking/README.md/0
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#!/usr/bin/env python import torch from transformers import CamembertForMaskedLM, CamembertTokenizer def fill_mask(masked_input, model, tokenizer, topk=5): # Adapted from https://github.com/pytorch/fairseq/blob/master/fairseq/models/roberta/hub_interface.py assert masked_input.count("<mask>") == 1 input_...
transformers/examples/legacy/run_camembert.py/0
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# coding=utf-8 # Copyright 2020 Huggingface # # 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/examples/legacy/seq2seq/old_test_fsmt_bleu_score.py/0
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#!/usr/bin/env python import io import json import subprocess pairs = [ ["en", "ru"], ["ru", "en"], ["en", "de"], ["de", "en"], ] n_objs = 8 def get_all_data(pairs, n_objs): text = {} for src, tgt in pairs: pair = f"{src}-{tgt}" cmd = f"sacrebleu -t wmt19 -l {pair} --echo s...
transformers/examples/legacy/seq2seq/test_data/fsmt/build-eval-data.py/0
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## Token classification Based on the scripts [`run_ner.py`](https://github.com/huggingface/transformers/blob/main/examples/legacy/token-classification/run_ner.py). The following examples are covered in this section: * NER on the GermEval 2014 (German NER) dataset * Emerging and Rare Entities task: WNUT’17 (English N...
transformers/examples/legacy/token-classification/README.md/0
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# 🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨🚨 # This file was automatically generated from examples/modular-transformers/modular_add_function.py. # Do NOT edit this file manually as any edits will be overwritten by the generatio...
transformers/examples/modular-transformers/modeling_add_function.py/0
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""" Here, because clip is not consistent with the use of the "Text" and "Vision" prefixes, we cannot simply use ``` class Multimodal2VisionModel(CLIPVisionModel): pass ``` with the hope that all dependencies will be renamed as `Multimodal2VisionClass`. For this reason, if we want consistency and use the "Vision" pa...
transformers/examples/modular-transformers/modular_multimodal2.py/0
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# 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/LICENSE-2.0 # # Unless r...
transformers/examples/pytorch/object-detection/run_object_detection_no_trainer.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/pytorch/speech-pretraining/README.md/0
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#!/usr/bin/env python # coding=utf-8 # Copyright 2020 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/text-classification/run_classification.py/0
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import argparse import logging import sys from unittest.mock import patch import run_glue_with_pabee from transformers.testing_utils import TestCasePlus logging.basicConfig(level=logging.DEBUG) logger = logging.getLogger() def get_setup_file(): parser = argparse.ArgumentParser() parser.add_argument("-f")...
transformers/examples/research_projects/bert-loses-patience/test_run_glue_with_pabee.py/0
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import argparse from copy import deepcopy import numpy as np from datasets import ClassLabel, DatasetDict, load_dataset from evaluate import load from transformers import ( AutoModelForSequenceClassification, AutoTokenizer, DataCollatorWithPadding, Trainer, TrainerCallback, TrainingArguments, ...
transformers/examples/research_projects/codeparrot/examples/train_complexity_predictor.py/0
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#!/bin/bash export CUDA_VISIBLE_DEVICES=0 PATH_TO_DATA=/h/xinji/projects/GLUE MODEL_TYPE=bert # bert or roberta MODEL_SIZE=base # base or large DATASET=MRPC # SST-2, MRPC, RTE, QNLI, QQP, or MNLI MODEL_NAME=${MODEL_TYPE}-${MODEL_SIZE} if [ $MODEL_TYPE = 'bert' ] then MODEL_NAME=${MODEL_NAME}-uncased fi ENTROPI...
transformers/examples/research_projects/deebert/entropy_eval.sh/0
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# coding=utf-8 # Copyright 2019-present, 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 a...
transformers/examples/research_projects/distillation/scripts/extract.py/0
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import torch from transformers import AutoTokenizer class FSNERTokenizerUtils: def __init__(self, pretrained_model_name_or_path): self.tokenizer = AutoTokenizer.from_pretrained(pretrained_model_name_or_path) def tokenize(self, x): """ Wrapper function for tokenizing query and support...
transformers/examples/research_projects/fsner/src/fsner/tokenizer_utils.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/research_projects/jax-projects/dataset-streaming/README.md/0
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import datasets import faiss import numpy as np import streamlit as st import torch from elasticsearch import Elasticsearch from eli5_utils import ( embed_questions_for_retrieval, make_qa_s2s_model, qa_s2s_generate, query_es_index, query_qa_dense_index, ) import transformers from transformers impor...
transformers/examples/research_projects/longform-qa/eli5_app.py/0
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import argparse import json from typing import List from ltp import LTP from transformers.models.bert.tokenization_bert import BertTokenizer def _is_chinese_char(cp): """Checks whether CP is the codepoint of a CJK character.""" # This defines a "chinese character" as anything in the CJK Unicode block: #...
transformers/examples/research_projects/mlm_wwm/run_chinese_ref.py/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/masked_run_squad.py/0
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from torch import nn class ClassificationHead(nn.Module): """Classification Head for transformer encoders""" def __init__(self, class_size, embed_size): super().__init__() self.class_size = class_size self.embed_size = embed_size # self.mlp1 = nn.Linear(embed_size, embed_size...
transformers/examples/research_projects/pplm/pplm_classification_head.py/0
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"""Finetuning script for RAG models. Adapted from examples.seq2seq.finetune.py""" import argparse import copy import json import logging import multiprocessing import os import random import shutil import sys import time from collections import defaultdict from pathlib import Path from typing import Any, Dict, List, T...
transformers/examples/research_projects/rag-end2end-retriever/finetune_rag.py/0
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# Intro Authors: @patrickvonplaten and @lhoestq Aimed at tackling the knowledge-intensive NLP tasks (think tasks a human wouldn't be expected to solve without access to external knowledge sources), RAG models are seq2seq models with access to a retrieval mechanism providing relevant context documents at training and ...
transformers/examples/research_projects/rag/README.md/0
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import re from filelock import FileLock try: import nltk NLTK_AVAILABLE = True except (ImportError, ModuleNotFoundError): NLTK_AVAILABLE = False if NLTK_AVAILABLE: with FileLock(".lock") as lock: nltk.download("punkt", quiet=True) def add_newline_to_end_of_each_sentence(x: str) -> str: ...
transformers/examples/research_projects/seq2seq-distillation/sentence_splitter.py/0
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import argparse from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig def generate(inputs, model, tokenizer, token_healing): input_ids = tokenizer(inputs, return_tensors="pt", padding=True, device_map="auto").input_ids generation_config = GenerationConfig( max_new_tokens=8, ...
transformers/examples/research_projects/token-healing/run_token_healing.py/0
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**NOTE**: This example is outdated and is not longer actively maintained. Please follow the new instructions of fine-tuning Wav2Vec2 [here](https://github.com/huggingface/transformers/blob/main/examples/pytorch/speech-recognition/README.md) ## Fine-tuning Wav2Vec2 The `run_asr.py` script allows one to fine-tune pret...
transformers/examples/research_projects/wav2vec2/README.md/0
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#!/usr/bin/env python # coding=utf-8 # Copyright 2023 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/tensorflow/language-modeling-tpu/prepare_tfrecord_shards.py/0
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#!/usr/bin/env python # HF Trainer benchmarking tool # # This tool can be used to run and compare multiple dimensions of the HF Trainers args. # # It then prints a report once in github format with all the information that needs to be shared # with others and second time in a console-friendly format, so it's easier to...
transformers/scripts/benchmark/trainer-benchmark.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/llm_engine.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/commands/download.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/data/datasets/language_modeling.py/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 applicabl...
transformers/src/transformers/generation/__init__.py/0
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from typing import Optional, Tuple import torch from ..utils import is_torch_flex_attn_available if is_torch_flex_attn_available(): from torch.nn.attention.flex_attention import flex_attention def flex_attention_forward( module: torch.nn.Module, query: torch.Tensor, key: torch.Tensor, value: t...
transformers/src/transformers/integrations/flex_attention.py/0
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__global__ void fast_hash_ver1_cuda_kernel( int *mask, // [batch_size, num_vector] float *vector, // [batch_size, num_vector, vector_dim] int *Dmat, // [3, num_part, vector_dim] int *hash_code, // [batch_size, num_vector, num_hash_f] int batch_size, int num_vector, int vector_dim, int...
transformers/src/transformers/kernels/yoso/fast_lsh_cumulation_cuda.h/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/modeling_tf_outputs.py/0
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