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{ "details": { "best_of_sequences": null, "finish_reason": "length", "generated_tokens": 10, "prefill": [ { "id": 17934, "logprob": null, "text": "Pour" }, { "id": 49833, "logprob": -10.5390625, "text": " dég" }, { "...
text-generation-inference/integration-tests/models/__snapshots__/test_bloom_560m_sharded/test_bloom_560m_sharded.json/0
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{ "details": { "best_of_sequences": null, "finish_reason": "length", "generated_tokens": 10, "prefill": [ { "id": 1, "logprob": null, "text": "<s>" }, { "id": 338, "logprob": -10.0078125, "text": "is" }, { "id": 2178...
text-generation-inference/integration-tests/models/__snapshots__/test_flash_medusa/test_flash_medusa_all_params.json/0
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{ "details": { "best_of_sequences": null, "finish_reason": "length", "generated_tokens": 60, "prefill": [ { "id": 589, "logprob": null, "text": "def" }, { "id": 1459, "logprob": -5.6328125, "text": " print" }, { "id"...
text-generation-inference/integration-tests/models/__snapshots__/test_flash_starcoder/test_flash_starcoder_default_params.json/0
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{ "details": { "best_of_sequences": null, "finish_reason": "eos_token", "generated_tokens": 7, "prefill": [ { "id": 0, "logprob": null, "text": "<pad>" } ], "seed": null, "tokens": [ { "id": 3, "logprob": -0.7001953, "specia...
text-generation-inference/integration-tests/models/__snapshots__/test_t5_sharded/test_t5_sharded.json/0
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import pytest @pytest.fixture(scope="module") def flash_starcoder_gptq_handle(launcher): with launcher("Narsil/starcoder-gptq", num_shard=2, quantize="gptq") as handle: yield handle @pytest.fixture(scope="module") async def flash_starcoder_gptq(flash_starcoder_gptq_handle): await flash_starcoder_gpt...
text-generation-inference/integration-tests/models/test_flash_starcoder_gptq.py/0
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import {check} from 'k6'; import http from 'k6/http'; import {Trend} from 'k6/metrics'; const host = __ENV.HOST || '127.0.0.1:3000'; const totalTime = new Trend('total_time', true); const validationTime = new Trend('validation_time', true); const queueTime = new Trend('queue_time', true); const inferenceTime = new Tr...
text-generation-inference/load_tests/starcoder_load.js/0
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/// Batching and inference logic use crate::validation::{Validation, ValidationError}; use crate::{ ChatTemplateInputs, Entry, GenerateRequest, GenerateStreamResponse, HubTokenizerConfig, Message, PrefillToken, Queue, Token, }; use futures::future::try_join_all; use minijinja::{Environment, ErrorKind, Template}...
text-generation-inference/router/src/infer.rs/0
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#include <ATen/Dispatch.h> #include <THC/THCAtomics.cuh> #include <ATen/ATen.h> #include <torch/torch.h> #include <vector> #include <optional> /** * Friendly reminder of how multithreading works in CUDA: https://developer.nvidia.com/blog/even-easier-introduction-cuda * Check example at https://github.com/thomasw21/Li...
text-generation-inference/server/custom_kernels/custom_kernels/fused_attention_cuda.cu/0
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// Adapted from turboderp exllama: https://github.com/turboderp/exllama #ifndef _util_cuh #define _util_cuh #include <cuda_runtime.h> #include <cuda_fp16.h> #include <cstdint> #include <cstdio> #if defined(USE_ROCM) #define cudaUnspecified hipErrorUnknown #else #define cudaUnspecified cudaErrorApiFailureBase #endif ...
text-generation-inference/server/exllama_kernels/exllama_kernels/util.cuh/0
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#ifndef _qdq_6_cuh #define _qdq_6_cuh #include "qdq_util.cuh" #include "../../config.h" #if QMODE_6BIT == 1 // Not implemented #else __forceinline__ __device__ void shuffle_6bit_16 ( uint32_t* q, int stride ) { } __forceinline__ __device__ void dequant_6bit_16 ( const uint32_t q_0, const uint32_...
text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/quant/qdq_6.cuh/0
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import pytest import torch from copy import copy from transformers import AutoTokenizer from text_generation_server.pb import generate_pb2 from text_generation_server.models.seq2seq_lm import Seq2SeqLM, Seq2SeqLMBatch @pytest.fixture(scope="session") def mt0_small_tokenizer(): tokenizer = AutoTokenizer.from_pr...
text-generation-inference/server/tests/models/test_seq2seq_lm.py/0
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# coding=utf-8 # Copyright 2022 EleutherAI and the HuggingFace Inc. team. All rights reserved. # # This code is based on EleutherAI's GPT-NeoX library and the GPT-NeoX # and OPT implementations in this library. It has been modified from its # original forms to accommodate minor architectural differences compared # to G...
text-generation-inference/server/text_generation_server/models/custom_modeling/flash_llama_modeling.py/0
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# imlementation of the PhiModel and PhiForCausalLM classes import torch import torch.distributed import math from torch import nn from typing import Optional, List, Tuple, Any from transformers.configuration_utils import PretrainedConfig from transformers.modeling_outputs import CausalLMOutputWithPast from text_gene...
text-generation-inference/server/text_generation_server/models/custom_modeling/phi_modeling.py/0
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import torch import torch.distributed from typing import Optional from transformers import ( AutoTokenizer, AutoConfig, ) from text_generation_server.models.custom_modeling.opt_modeling import OPTForCausalLM from text_generation_server.models import CausalLM from text_generation_server.utils import ( init...
text-generation-inference/server/text_generation_server/models/opt.py/0
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import torch from exllama_kernels import make_q4, q4_matmul, prepare_buffers, set_tuning_params # Dummy tensor to pass instead of g_idx since there is no way to pass "None" to a C++ extension none_tensor = torch.empty((1, 1), device="meta") def ext_make_q4(qweight, qzeros, scales, g_idx, device): """Construct Q4...
text-generation-inference/server/text_generation_server/utils/gptq/exllama.py/0
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import subprocess import argparse def main(): parser = argparse.ArgumentParser() parser.add_argument("--check", action="store_true") args = parser.parse_args() output = subprocess.check_output(["text-generation-launcher", "--help"]).decode( "utf-8" ) wrap_code_blocks_flag = "<!-- WR...
text-generation-inference/update_doc.py/0
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## How to release # Before the release Simple checklist on how to make releases for `tokenizers`. - Freeze `master` branch. - Run all tests (Check CI has properly run) - If any significant work, check benchmarks: - `cd tokenizers && cargo bench` (needs to be run on latest release tag to measure difference if it's ...
tokenizers/RELEASE.md/0
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/* eslint-disable */ var globRequire = require console.log = (..._args: any[]) => {} describe('quicktourExample', () => { function require(mod: string) { if (mod.startsWith('tokenizers')) { return globRequire('../../') } else { return globRequire(mod) } } it.skip('trains the tokenizer',...
tokenizers/bindings/node/examples/documentation/quicktour.test.ts/0
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{ "name": "tokenizers-android-arm-eabi", "version": "0.13.4-rc1", "os": [ "android" ], "cpu": [ "arm" ], "main": "tokenizers.android-arm-eabi.node", "files": [ "tokenizers.android-arm-eabi.node" ], "description": "Tokenizers platform specific bindings", "keywords": [ "napi-rs", ...
tokenizers/bindings/node/npm/android-arm-eabi/package.json/0
{ "file_path": "tokenizers/bindings/node/npm/android-arm-eabi/package.json", "repo_id": "tokenizers", "token_count": 269 }
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{ "name": "tokenizers-linux-x64-gnu", "version": "0.13.4-rc1", "os": [ "linux" ], "cpu": [ "x64" ], "main": "tokenizers.linux-x64-gnu.node", "files": [ "tokenizers.linux-x64-gnu.node" ], "description": "Tokenizers platform specific bindings", "keywords": [ "napi-rs", "NAPI", ...
tokenizers/bindings/node/npm/linux-x64-gnu/package.json/0
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use crate::arc_rwlock_serde; use napi::bindgen_prelude::*; use napi_derive::napi; use serde::{Deserialize, Serialize}; use std::sync::{Arc, RwLock}; use tk::normalizers::NormalizerWrapper; use tk::NormalizedString; use tokenizers as tk; /// Normalizer #[derive(Debug, Clone, Serialize, Deserialize)] #[napi] pub struct ...
tokenizers/bindings/node/src/normalizers.rs/0
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include Cargo.toml include pyproject.toml include rust-toolchain include ../../LICENSE recursive-include src * recursive-include tokenizers-lib * recursive-exclude tokenizers-lib/target *
tokenizers/bindings/python/MANIFEST.in/0
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from typing import Dict, Iterator, List, Optional, Union from tokenizers import AddedToken, Tokenizer, decoders, trainers from tokenizers.models import WordPiece from tokenizers.normalizers import BertNormalizer from tokenizers.pre_tokenizers import BertPreTokenizer from tokenizers.processors import BertProcessing fr...
tokenizers/bindings/python/py_src/tokenizers/implementations/bert_wordpiece.py/0
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# Generated content DO NOT EDIT from .. import trainers Trainer = trainers.Trainer BpeTrainer = trainers.BpeTrainer UnigramTrainer = trainers.UnigramTrainer WordLevelTrainer = trainers.WordLevelTrainer WordPieceTrainer = trainers.WordPieceTrainer
tokenizers/bindings/python/py_src/tokenizers/trainers/__init__.py/0
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use pyo3::prelude::*; use tk::Token; #[pyclass(module = "tokenizers", name = "Token")] #[derive(Clone)] pub struct PyToken { token: Token, } impl From<Token> for PyToken { fn from(token: Token) -> Self { Self { token } } } impl From<PyToken> for Token { fn from(token: PyToken) -> Self { ...
tokenizers/bindings/python/src/token.rs/0
{ "file_path": "tokenizers/bindings/python/src/token.rs", "repo_id": "tokenizers", "token_count": 439 }
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import json import pickle import pytest from tokenizers.pre_tokenizers import ( BertPreTokenizer, ByteLevel, CharDelimiterSplit, Digits, Metaspace, PreTokenizer, Punctuation, Sequence, Split, UnicodeScripts, Whitespace, WhitespaceSplit, ) class TestByteLevel: def ...
tokenizers/bindings/python/tests/bindings/test_pre_tokenizers.py/0
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# Minimal makefile for Sphinx documentation # # You can set these variables from the command line, and also # from the environment for those with `?=` SPHINXOPTS ?= SPHINXBUILD ?= sphinx-build BUILDDIR ?= build SOURCEDIR = source # Put it first so that "make" without argument is like "make html_all". h...
tokenizers/docs/Makefile/0
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<!-- DISABLE-FRONTMATTER-SECTIONS --> # Tokenizers Fast State-of-the-art tokenizers, optimized for both research and production [🤗 Tokenizers](https://github.com/huggingface/tokenizers) provides an implementation of today's most used tokenizers, with a focus on performance and versatility. These tokenizers are also...
tokenizers/docs/source-doc-builder/index.mdx/0
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Input sequences ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ These types represent all the different kinds of sequence that can be used as input of a Tokenizer. Globally, any sequence can be either a string or a list of strings, according to the operating mode of...
tokenizers/docs/source/api/python.inc/0
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#!/usr/bin/env node const { spawn } = require("child_process"); const fs = require("fs"); let folderName = '.'; if (process.argv.length >= 3) { folderName = process.argv[2]; if (!fs.existsSync(folderName)) { fs.mkdirSync(folderName); } } const clone = spawn("git", ["clone", "https://github.com/rustwasm/cr...
tokenizers/tokenizers/examples/unstable_wasm/www/.bin/create-wasm-app.js/0
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use super::model::Unigram; use serde::{ de::{Error, MapAccess, Visitor}, ser::SerializeStruct, Deserialize, Deserializer, Serialize, Serializer, }; impl Serialize for Unigram { fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error> where S: Serializer, { let mut model ...
tokenizers/tokenizers/src/models/unigram/serialization.rs/0
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use serde::{Deserialize, Serialize}; use crate::normalizers::NormalizerWrapper; use crate::tokenizer::{NormalizedString, Normalizer, Result}; use crate::utils::macro_rules_attribute; #[derive(Clone, Deserialize, Debug, Serialize)] #[serde(tag = "type")] /// Allows concatenating multiple other Normalizer as a Sequence...
tokenizers/tokenizers/src/normalizers/utils.rs/0
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use crate::processors::byte_level::process_offsets; use crate::tokenizer::{Encoding, PostProcessor, Result}; use serde::{Deserialize, Serialize}; use std::collections::HashMap; use std::iter::FromIterator; #[derive(Serialize, Deserialize, Debug, Clone, PartialEq, Eq)] #[serde(tag = "type")] pub struct RobertaProcessin...
tokenizers/tokenizers/src/processors/roberta.rs/0
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use crate::parallelism::*; use crate::tokenizer::{Encoding, Result}; use serde::{Deserialize, Serialize}; /// The various possible padding directions. #[derive(Debug, Clone, Copy, Serialize, Deserialize)] pub enum PaddingDirection { Left, Right, } impl std::convert::AsRef<str> for PaddingDirection { fn as...
tokenizers/tokenizers/src/utils/padding.rs/0
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cff-version: "1.2.0" date-released: 2020-10 message: "If you use this software, please cite it using these metadata." title: "Transformers: State-of-the-Art Natural Language Processing" url: "https://github.com/huggingface/transformers" authors: - family-names: Wolf given-names: Thomas - family-names: Debut ...
transformers/CITATION.cff/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 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...
transformers/docs/source/de/peft.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/attention.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/glossary.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/main_classes/agent.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/main_classes/quantization.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/model_doc/camembert.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/cvt.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/flava.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/levit.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/model_doc/mbart.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/model_doc/mpt.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/owlvit.md/0
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<!--Copyright 2024 The Qwen 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 applic...
transformers/docs/source/en/model_doc/qwen2.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/segformer.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/t5v1.1.md/0
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# docstyle-ignore INSTALL_CONTENT = """ # Installazione di Transformers ! pip install transformers datasets # Per installare dalla fonte invece dell'ultima versione rilasciata, commenta il comando sopra e # rimuovi la modalità commento al comando seguente. # ! pip install git+https://github.com/huggingface/transformers...
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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 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 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 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 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 ...
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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 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 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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- sections: - local: index title: 🤗 Transformers title: Get started
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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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# 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...
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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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#!/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...
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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.", ...
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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 "...
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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 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 ...
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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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# coding=utf-8 # Copyright 2018 HuggingFace 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 # # Unless required by applicable law or a...
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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...
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# Examples In this folder we showcase some examples to use code models for downstream tasks. ## Complexity prediction In this task we want to predict the complexity of Java programs in [CodeComplex](https://huggingface.co/datasets/codeparrot/codecomplex) dataset. Using Hugging Face `trainer`, we finetuned [multilingua...
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import gym import numpy as np import torch from mujoco_py import GlfwContext from transformers import DecisionTransformerModel GlfwContext(offscreen=True) # Create a window to init GLFW. def get_action(model, states, actions, rewards, returns_to_go, timesteps): # we don't care about the past rewards in this m...
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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...
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from .model import FSNERModel from .tokenizer_utils import FSNERTokenizerUtils __all__ = ["FSNERModel", "FSNERTokenizerUtils"]
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command: - python3 - train.py method: random parameters: lr: values: [4e-5, 3e-5] warmup_steps: values: [20000, 15000, 10000, 5000] weight_decay: distribution: normal mu: 1e-2 sigma: 2e-3 metric: ...
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#!/usr/bin/env python # coding=utf-8 # 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-...
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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 ...
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# coding=utf-8 # Copyright 2020-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...
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import logging import os from dataclasses import dataclass, field from functools import partial from pathlib import Path from tempfile import TemporaryDirectory from typing import List, Optional import faiss import torch from datasets import Features, Sequence, Value, load_dataset from transformers import DPRContextE...
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import argparse import logging import os import sys import tempfile from pathlib import Path import lightning_base import pytest import pytorch_lightning as pl import torch from convert_pl_checkpoint_to_hf import convert_pl_to_hf from distillation import distill_main from finetune import SummarizationModule, main from...
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#!/usr/bin/env bash python run_asr.py \ --output_dir="./wav2vec2-base-100h" \ --num_train_epochs="30" \ --per_device_train_batch_size="32" \ --per_device_eval_batch_size="32" \ --evaluation_strategy="steps" \ --save_total_limit="3" \ --save_steps="500" \ --eval_steps="100" \ --logging_steps="50" \ --learning_rate="5e-4...
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# Zero-shot classifier distillation Author: @joeddav This script provides a way to improve the speed and memory performance of a zero-shot classifier by training a more efficient student model from the zero-shot teacher's predictions over an unlabeled dataset. The zero-shot classification pipeline uses a model pre-...
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