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# Fork that adds only the correct stream to this kernel in order # to make cuda graphs work. awq_commit := bd1dc2d5254345cc76ab71894651fb821275bdd4 awq: rm -rf llm-awq git clone https://github.com/huggingface/llm-awq build-awq: awq cd llm-awq/ && git fetch && git checkout $(awq_commit) cd llm-awq/awq/kernels && p...
text-generation-inference/server/Makefile-awq/0
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// Adapted from turboderp exllama: https://github.com/turboderp/exllama #ifndef _cuda_buffers_cuh #define _cuda_buffers_cuh #include <cuda_runtime.h> #include <cuda_fp16.h> #include <cstdint> #include <cstdio> const int CUDA_MAX_DEVICES = 16; // #ifndef _cuda_buffers_cu // extern __constant__ half2 q4_table[16][256...
text-generation-inference/server/exllama_kernels/exllama_kernels/cuda_buffers.cuh/0
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#ifndef _matrix_view_cuh #define _matrix_view_cuh #include <cuda_runtime.h> #include <cuda_fp16.h> #include "quant/qdq_util.cuh" class MatrixView_half { public: const half* data; const int height; const int width; __device__ __forceinline__ MatrixView_half(const half* data, const int height, const i...
text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/matrix_view.cuh/0
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from setuptools import setup from torch.utils.cpp_extension import BuildExtension, CUDAExtension import torch extra_cuda_cflags = ["-lineinfo", "-O3"] if torch.version.hip: extra_cuda_cflags += ["-DHIPBLAS_USE_HIP_HALF"] extra_compile_args = { "nvcc": extra_cuda_cflags, } setup( name="exllamav2_kernels"...
text-generation-inference/server/exllamav2_kernels/setup.py/0
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import torch from text_generation_server.utils.tokens import ( StopSequenceCriteria, StoppingCriteria, FinishReason, batch_top_tokens, ) def test_stop_sequence_criteria(): criteria = StopSequenceCriteria("/test;") assert not criteria("/") assert not criteria("/test") assert criteria("...
text-generation-inference/server/tests/utils/test_tokens.py/0
{ "file_path": "text-generation-inference/server/tests/utils/test_tokens.py", "repo_id": "text-generation-inference", "token_count": 1427 }
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from typing import Optional from contextvars import ContextVar from contextlib import contextmanager import flashinfer import torch prefill_state: ContextVar[flashinfer.BatchPrefillWithRaggedKVCacheWrapper] = ContextVar( "prefill_state" ) prefill_with_paged_kv_state: ContextVar[ flashinfer.BatchPrefillWithPa...
text-generation-inference/server/text_generation_server/layers/attention/flashinfer.py/0
{ "file_path": "text-generation-inference/server/text_generation_server/layers/attention/flashinfer.py", "repo_id": "text-generation-inference", "token_count": 3150 }
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import torch # copied from https://github.com/openppl-public/ppq/blob/master/ppq/quantization/measure/norm.py def torch_snr_error( y_pred: torch.Tensor, y_real: torch.Tensor, reduction: str = "mean" ) -> torch.Tensor: """ Compute SNR between y_pred(tensor) and y_real(tensor) SNR can be calcualted as ...
text-generation-inference/server/text_generation_server/layers/gptq/utils.py/0
{ "file_path": "text-generation-inference/server/text_generation_server/layers/gptq/utils.py", "repo_id": "text-generation-inference", "token_count": 742 }
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import torch import time import torch.distributed from dataclasses import dataclass from opentelemetry import trace from transformers import ( AutoConfig, AutoTokenizer, AutoModelForCausalLM, PreTrainedTokenizerBase, ) from typing import Optional, Tuple, List, Type, Dict from text_generation_server.ut...
text-generation-inference/server/text_generation_server/models/causal_lm.py/0
{ "file_path": "text-generation-inference/server/text_generation_server/models/causal_lm.py", "repo_id": "text-generation-inference", "token_count": 16948 }
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import torch import torch.distributed from torch import nn from transformers.activations import ACT2FN from transformers.configuration_utils import PretrainedConfig from typing import Optional, List, Tuple from text_generation_server.layers.attention import ( paged_attention, attention, reshape_and_cache,...
text-generation-inference/server/text_generation_server/models/custom_modeling/flash_phi_modeling.py/0
{ "file_path": "text-generation-inference/server/text_generation_server/models/custom_modeling/flash_phi_modeling.py", "repo_id": "text-generation-inference", "token_count": 6605 }
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# coding=utf-8 # Copyright 2022 The Fairseq Authors 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/...
text-generation-inference/server/text_generation_server/models/custom_modeling/opt_modeling.py/0
{ "file_path": "text-generation-inference/server/text_generation_server/models/custom_modeling/opt_modeling.py", "repo_id": "text-generation-inference", "token_count": 15778 }
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# Origin: https://github.com/predibase/lorax # Path: lorax/server/lorax_server/utils/segments.py # License: Apache License Version 2.0, January 2004 from typing import List, Tuple, Union import torch def find_segments( adapter_indices: Union[torch.Tensor, List[int]] ) -> Tuple[List[int], List[int]]: ...
text-generation-inference/server/text_generation_server/utils/segments.py/0
{ "file_path": "text-generation-inference/server/text_generation_server/utils/segments.py", "repo_id": "text-generation-inference", "token_count": 1081 }
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exclude = ["node_modules/**/*.toml"] # https://taplo.tamasfe.dev/configuration/formatter-options.html [formatting] align_entries = true indent_tables = true reorder_keys = true
tokenizers/bindings/node/.taplo.toml/0
{ "file_path": "tokenizers/bindings/node/.taplo.toml", "repo_id": "tokenizers", "token_count": 66 }
277
import { bpeDecoder, byteFallbackDecoder, ctcDecoder, fuseDecoder, metaspaceDecoder, replaceDecoder, sequenceDecoder, stripDecoder, wordPieceDecoder, } from '../../' describe('wordPieceDecoder', () => { it('accepts `undefined` as first parameter', () => { expect(wordPieceDecoder(undefined)).toB...
tokenizers/bindings/node/lib/bindings/decoders.test.ts/0
{ "file_path": "tokenizers/bindings/node/lib/bindings/decoders.test.ts", "repo_id": "tokenizers", "token_count": 1393 }
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# `tokenizers-freebsd-x64` This is the **x86_64-unknown-freebsd** binary for `tokenizers`
tokenizers/bindings/node/npm/freebsd-x64/README.md/0
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# `tokenizers-win32-x64-msvc` This is the **x86_64-pc-windows-msvc** binary for `tokenizers`
tokenizers/bindings/node/npm/win32-x64-msvc/README.md/0
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use crate::models::Model; use napi_derive::napi; use std::sync::{Arc, RwLock}; use tokenizers as tk; use tokenizers::models::TrainerWrapper; #[napi] pub struct Trainer { trainer: Option<Arc<RwLock<TrainerWrapper>>>, } impl From<TrainerWrapper> for Trainer { fn from(trainer: TrainerWrapper) -> Self { Self { ...
tokenizers/bindings/node/src/trainers.rs/0
{ "file_path": "tokenizers/bindings/node/src/trainers.rs", "repo_id": "tokenizers", "token_count": 641 }
281
import argparse import glob from tokenizers import BertWordPieceTokenizer parser = argparse.ArgumentParser() parser.add_argument( "--files", default=None, metavar="path", type=str, required=True, help="The files to use as training; accept '**/*.txt' type of patterns \ ...
tokenizers/bindings/python/examples/train_bert_wordpiece.py/0
{ "file_path": "tokenizers/bindings/python/examples/train_bert_wordpiece.py", "repo_id": "tokenizers", "token_count": 472 }
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# Generated content DO NOT EDIT class Model: """ Base class for all models The model represents the actual tokenization algorithm. This is the part that will contain and manage the learned vocabulary. This class cannot be constructed directly. Please use one of the concrete models. """ def...
tokenizers/bindings/python/py_src/tokenizers/models/__init__.pyi/0
{ "file_path": "tokenizers/bindings/python/py_src/tokenizers/models/__init__.pyi", "repo_id": "tokenizers", "token_count": 7626 }
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import tokenizers from argparse import ArgumentParser import sentencepiece as spm from collections import Counter import json import os import datetime try: from termcolor import colored has_color = True except Exception: has_color = False def main(): parser = ArgumentParser("SentencePiece parity ch...
tokenizers/bindings/python/scripts/spm_parity_check.py/0
{ "file_path": "tokenizers/bindings/python/scripts/spm_parity_check.py", "repo_id": "tokenizers", "token_count": 4110 }
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use tokenizers as tk; use pyo3::exceptions; use pyo3::prelude::*; use pyo3::types::*; use super::{ DestroyPtr, PyNormalizedString, PyNormalizedStringRefMut, RefMutContainer, RefMutGuard, }; use crate::encoding::PyEncoding; use crate::error::ToPyResult; use crate::token::PyToken; use tk::{OffsetReferential, Offset...
tokenizers/bindings/python/src/utils/pretokenization.rs/0
{ "file_path": "tokenizers/bindings/python/src/utils/pretokenization.rs", "repo_id": "tokenizers", "token_count": 4930 }
285
from tokenizers import Tokenizer from ..utils import data_dir, doc_pipeline_bert_tokenizer, doc_wiki_tokenizer disable_printing = True original_print = print def print(*args, **kwargs): if not disable_printing: original_print(*args, **kwargs) class TestPipeline: def test_pipeline(self, doc_wiki_to...
tokenizers/bindings/python/tests/documentation/test_pipeline.py/0
{ "file_path": "tokenizers/bindings/python/tests/documentation/test_pipeline.py", "repo_id": "tokenizers", "token_count": 3351 }
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# Encode Inputs <tokenizerslangcontent> <python> These types represent all the different kinds of input that a [`~tokenizers.Tokenizer`] accepts when using [`~tokenizers.Tokenizer.encode_batch`]. ## TextEncodeInput[[[[tokenizers.TextEncodeInput]]]] <code>tokenizers.TextEncodeInput</code> Represents a textual input ...
tokenizers/docs/source-doc-builder/api/encode-inputs.mdx/0
{ "file_path": "tokenizers/docs/source-doc-builder/api/encode-inputs.mdx", "repo_id": "tokenizers", "token_count": 716 }
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from collections import defaultdict, abc from typing import cast from docutils import nodes from docutils.parsers.rst import Directive import sphinx from sphinx.locale import _ from sphinx.util.docutils import SphinxDirective from sphinx.errors import ExtensionError from conf import languages as LANGUAGES logger = ...
tokenizers/docs/source/_ext/entities.py/0
{ "file_path": "tokenizers/docs/source/_ext/entities.py", "repo_id": "tokenizers", "token_count": 4032 }
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.. entities:: python :global: class class classmethod class method Tokenizer :class:`~tokenizers.Tokenizer` Tokenizer.train :meth:`~tokenizers.Tokenizer.train` Tokenizer.save :meth:`~tokenizers.Tokenizer.save` Tokenizer.from_file :meth:`~toke...
tokenizers/docs/source/entities.inc/0
{ "file_path": "tokenizers/docs/source/entities.inc", "repo_id": "tokenizers", "token_count": 2078 }
289
#[macro_use] extern crate criterion; mod common; use std::fs::File; use std::io::{BufRead, BufReader}; use std::path::Path; use criterion::Criterion; use tokenizers::models::bpe::{BpeTrainerBuilder, BPE}; use tokenizers::models::TrainerWrapper; use tokenizers::pre_tokenizers::byte_level::ByteLevel; use tokenizers::p...
tokenizers/tokenizers/benches/bpe_benchmark.rs/0
{ "file_path": "tokenizers/tokenizers/benches/bpe_benchmark.rs", "repo_id": "tokenizers", "token_count": 1631 }
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use crate::tokenizer::{Decoder, Result}; use serde::{Deserialize, Serialize}; #[derive(Deserialize, Clone, Debug, Serialize, Default)] /// Strip is a simple trick which converts tokens looking like `<0x61>` /// to pure bytes, and attempts to make them into a string. If the tokens /// cannot be decoded you will get � ...
tokenizers/tokenizers/src/decoders/strip.rs/0
{ "file_path": "tokenizers/tokenizers/src/decoders/strip.rs", "repo_id": "tokenizers", "token_count": 1217 }
291
use super::{super::OrderedVocabIter, WordLevel, WordLevelBuilder}; use serde::{ de::{MapAccess, Visitor}, ser::SerializeStruct, Deserialize, Deserializer, Serialize, Serializer, }; use std::collections::HashSet; impl Serialize for WordLevel { fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Er...
tokenizers/tokenizers/src/models/wordlevel/serialization.rs/0
{ "file_path": "tokenizers/tokenizers/src/models/wordlevel/serialization.rs", "repo_id": "tokenizers", "token_count": 2084 }
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use serde::{Deserialize, Serialize}; use crate::tokenizer::{PreTokenizedString, PreTokenizer, Result, SplitDelimiterBehavior}; use crate::utils::macro_rules_attribute; #[derive(Copy, Clone, Debug, PartialEq, Eq)] #[non_exhaustive] #[macro_rules_attribute(impl_serde_type!)] pub struct CharDelimiterSplit { pub deli...
tokenizers/tokenizers/src/pre_tokenizers/delimiter.rs/0
{ "file_path": "tokenizers/tokenizers/src/pre_tokenizers/delimiter.rs", "repo_id": "tokenizers", "token_count": 296 }
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use super::{ normalizer::Range, Model, NormalizedString, Normalizer, Offsets, PreTokenizedString, Token, }; use aho_corasick::{AhoCorasick, AhoCorasickBuilder, MatchKind}; use regex::Regex; use serde::{ser::SerializeSeq, Deserialize, Serialize, Serializer}; use std::collections::{HashMap, HashSet}; /// Represent a...
tokenizers/tokenizers/src/tokenizer/added_vocabulary.rs/0
{ "file_path": "tokenizers/tokenizers/src/tokenizer/added_vocabulary.rs", "repo_id": "tokenizers", "token_count": 17733 }
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use crate::tokenizer::{Encoding, Result}; use serde::{Deserialize, Serialize}; use std::cmp; use std::mem; #[derive(Debug, Clone, Copy, PartialEq, Serialize, Deserialize, Eq, Default)] pub enum TruncationDirection { Left, #[default] Right, } impl std::convert::AsRef<str> for TruncationDirection { fn a...
tokenizers/tokenizers/src/utils/truncation.rs/0
{ "file_path": "tokenizers/tokenizers/src/utils/truncation.rs", "repo_id": "tokenizers", "token_count": 5473 }
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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
{ "file_path": "transformers/SECURITY.md", "repo_id": "transformers", "token_count": 553 }
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FROM python:3.10-slim ENV PYTHONDONTWRITEBYTECODE=1 ARG REF=main USER root RUN apt-get update && apt-get install -y --no-install-recommends libsndfile1-dev espeak-ng time git g++ pkg-config openssh-client git RUN apt-get install -y cmake ENV UV_PYTHON=/usr/local/bin/python RUN pip --no-cache-dir install uv && uv venv...
transformers/docker/tf-light.dockerfile/0
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#!/bin/bash source ~/.bashrc echo "running docker-entrypoint.sh" conda activate container echo $KUBE_GOOGLE_CLOUD_TPU_ENDPOINTS echo "printed TPU info" export XRT_TPU_CONFIG="tpu_worker;0;${KUBE_GOOGLE_CLOUD_TPU_ENDPOINTS:7}" exec "$@"#!/bin/bash
transformers/docker/transformers-pytorch-tpu/docker-entrypoint.sh/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
{ "file_path": "transformers/docs/source/de/model_sharing.md", "repo_id": "transformers", "token_count": 4287 }
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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/agents.md/0
{ "file_path": "transformers/docs/source/en/agents.md", "repo_id": "transformers", "token_count": 7222 }
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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
{ "file_path": "transformers/docs/source/en/generation_strategies.md", "repo_id": "transformers", "token_count": 8119 }
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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 to...
transformers/docs/source/en/llm_optims.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/en/main_classes/output.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/bartpho.md/0
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<!--Copyright 2023 The Intel Labs Team Authors, The Microsoft Research Team Authors and 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...
transformers/docs/source/en/model_doc/bridgetower.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/convnext.md/0
{ "file_path": "transformers/docs/source/en/model_doc/convnext.md", "repo_id": "transformers", "token_count": 1215 }
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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/ernie.md/0
{ "file_path": "transformers/docs/source/en/model_doc/ernie.md", "repo_id": "transformers", "token_count": 1417 }
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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 agree...
transformers/docs/source/en/model_doc/gemma2.md/0
{ "file_path": "transformers/docs/source/en/model_doc/gemma2.md", "repo_id": "transformers", "token_count": 736 }
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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/hiera.md/0
{ "file_path": "transformers/docs/source/en/model_doc/hiera.md", "repo_id": "transformers", "token_count": 1119 }
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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/layoutxlm.md/0
{ "file_path": "transformers/docs/source/en/model_doc/layoutxlm.md", "repo_id": "transformers", "token_count": 981 }
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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/model_doc/mms.md/0
{ "file_path": "transformers/docs/source/en/model_doc/mms.md", "repo_id": "transformers", "token_count": 4924 }
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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/model_doc/nllb-moe.md/0
{ "file_path": "transformers/docs/source/en/model_doc/nllb-moe.md", "repo_id": "transformers", "token_count": 2003 }
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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
{ "file_path": "transformers/docs/source/en/model_doc/perceiver.md", "repo_id": "transformers", "token_count": 2762 }
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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/qwen2_vl.md/0
{ "file_path": "transformers/docs/source/en/model_doc/qwen2_vl.md", "repo_id": "transformers", "token_count": 4619 }
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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/vit.md/0
{ "file_path": "transformers/docs/source/en/model_doc/vit.md", "repo_id": "transformers", "token_count": 3788 }
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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/en/model_doc/xlm-prophetnet.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/pipeline_tutorial.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/quicktour.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 ...
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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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<!--⚠️ 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'...
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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 ...
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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 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...
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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...
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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 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...
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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...
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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...
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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...
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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...
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transformers/docs/source/ko/quantization/bitsandbytes.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...
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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/visual_question_answering.md/0
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- sections: - local: index title: 🤗 Transformers - local: quicktour title: Tour rápido - local: installation title: Instalação title: Início - sections: - local: pipeline_tutorial title: Pipelines para inferência - local: training title: Fine-tuning de um modelo pré-treinado - local: ...
transformers/docs/source/pt/_toctree.yml/0
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- sections: - local: index title: 🤗 Transformers - local: quicktour title: త్వరిత పర్యటన title: ప్రారంభించడానికి
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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 agree...
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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/tflite.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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#!/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/flax/speech-recognition/run_flax_speech_recognition_seq2seq.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/examples/legacy/benchmarking/plot_csv_file.py/0
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#!/usr/bin/env python import argparse import json from typing import List from ltp import LTP from transformers 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: # https...
transformers/examples/legacy/run_chinese_ref.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/examples/legacy/seq2seq/old_test_seq2seq_examples.py/0
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{ "en-ru": { "src": [ "Welsh AMs worried about 'looking like muppets'", "There is consternation among some AMs at a suggestion their title should change to MWPs (Member of the Welsh Parliament).", "It has arisen because of plans to change the name of the assembly to the Welsh Parliament.", ...
transformers/examples/legacy/seq2seq/test_data/fsmt/fsmt_val_data.json/0
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## The relevant files are currently on a shared Google ## drive at https://drive.google.com/drive/folders/1kC0I2UGl2ltrluI9NqDjaQJGw5iliw_J ## Monitor for changes and eventually migrate to use the `datasets` library curl -L 'https://drive.google.com/uc?export=download&id=1Jjhbal535VVz2ap4v4r_rN1UEHTdLK5P' \ | grep -v "...
transformers/examples/legacy/token-classification/run.sh/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/image-classification/README.md/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/pytorch/language-modeling/run_clm_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/question-answering/README.md/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/pytorch/speech-pretraining/run_wav2vec2_pretraining_no_trainer.py/0
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# 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/LICENSE-2.0 # # Unless r...
transformers/examples/pytorch/text-classification/run_glue_no_trainer.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/examples/pytorch/xla_spawn.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/examples/research_projects/bertabs/convert_bertabs_original_pytorch_checkpoint.py/0
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import logging import os import time from argparse import Namespace from pathlib import Path import datasets import torch from accelerate import Accelerator, DistributedType from accelerate.utils import ProjectConfiguration from arguments import TrainingArguments from datasets import load_dataset from huggingface_hub ...
transformers/examples/research_projects/codeparrot/scripts/codeparrot_training.py/0
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{ "activation": "gelu", "attention_dropout": 0.1, "dim": 768, "dropout": 0.1, "hidden_dim": 3072, "initializer_range": 0.02, "max_position_embeddings": 512, "n_heads": 12, "n_layers": 6, "sinusoidal_pos_embds": true, "tie_weights_": true, "vocab_size": 28996 }
transformers/examples/research_projects/distillation/training_configs/distilbert-base-cased.json/0
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# 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-2.0 # # Unless requir...
transformers/examples/research_projects/jax-projects/hybrid_clip/modeling_hybrid_clip.py/0
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import unicodedata from dataclasses import dataclass from typing import Optional, Union import numpy as np from transformers.data.data_collator import DataCollatorMixin from transformers.file_utils import PaddingStrategy from transformers.tokenization_utils_base import PreTrainedTokenizerBase def padding_tensor(seq...
transformers/examples/research_projects/luke/luke_utils.py/0
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# coding=utf-8 # Copyright (c) Facebook, Inc. and its affiliates. # Copyright (c) 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...
transformers/examples/research_projects/mm-imdb/utils_mmimdb.py/0
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""" Code to remove duplicate initializers to reduce ONNX model size. """ import os import numpy import onnx def _is_equal_tensor_proto(a, b): name_a = a.name name_b = b.name a.name = "" b.name = "" res = a == b a.name = name_a b.name = name_b return res def _node_replace_input_...
transformers/examples/research_projects/onnx/summarization/bart_onnx/reduce_onnx_size.py/0
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