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{ "details": { "best_of_sequences": null, "finish_reason": "length", "generated_tokens": 10, "prefill": [ { "id": 50278, "logprob": null, "text": "<|USER|>" }, { "id": 1276, "logprob": -4.5546875, "text": "What" }, { ...
text-generation-inference/integration-tests/models/__snapshots__/test_neox/test_neox.json/0
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import pytest @pytest.fixture(scope="module") def flash_llama_chat_handle(launcher): with launcher( "TinyLlama/TinyLlama-1.1B-Chat-v1.0", num_shard=2, disable_grammar_support=False ) as handle: yield handle @pytest.fixture(scope="module") async def flash_llama_chat(flash_llama_chat_handle): ...
text-generation-inference/integration-tests/models/test_chat_llama.py/0
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import pytest @pytest.fixture(scope="module") def flash_llama_marlin24_handle(launcher): with launcher( "nm-testing/Llama-2-7b-pruned2.4-Marlin_24", quantize="marlin" ) as handle: yield handle @pytest.fixture(scope="module") async def flash_llama_marlin(flash_llama_marlin24_handle): awai...
text-generation-inference/integration-tests/models/test_flash_llama_marlin_24.py/0
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import pytest import base64 # TODO fix the server parsser to count inline image tokens correctly def get_chicken(): with open("integration-tests/images/chicken_on_money.png", "rb") as image_file: encoded_string = base64.b64encode(image_file.read()) return f"data:image/png;base64,{encoded_string.decode...
text-generation-inference/integration-tests/models/test_llava_next.py/0
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use std::fmt; use std::process::Command; pub(crate) struct Env { cargo_target: &'static str, cargo_version: &'static str, git_sha: &'static str, docker_label: &'static str, nvidia_env: String, xpu_env: String, } impl Env { pub fn new() -> Self { let nvidia_env = nvidia_smi(); ...
text-generation-inference/launcher/src/env_runtime.rs/0
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use crate::infer::InferError; use crate::{ FunctionDefinition, FunctionRef, FunctionsMap, JsonSchemaTool, Properties, Tool, ToolChoice, ToolType, }; use serde_json::{json, Map, Value}; use std::collections::HashMap; pub(crate) struct ToolGrammar {} impl ToolGrammar { // find a tool by name fn find_too...
text-generation-inference/router/src/infer/tool_grammar.rs/0
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eetq_commit := 1657b1504faa359e2ce0ac02999439d7ac8c74c0 eetq: # Clone eetq pip install packaging git clone https://github.com/NetEase-FuXi/EETQ.git eetq build-eetq: eetq cd eetq && git fetch && git checkout $(eetq_commit) && git submodule update --init --recursive cd eetq && python setup.py build install-eet...
text-generation-inference/server/Makefile-eetq/0
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// Adapted from turboderp exllama: https://github.com/turboderp/exllama #include "column_remap.cuh" #include "../util.cuh" const int SHUF_BLOCKSIZE_X = 256; const int SHUF_BLOCKSIZE_Y = 16; __global__ void column_remap_kernel ( const half* __restrict__ x, half* __restrict__ x_new, const int x_width, ...
text-generation-inference/server/exllama_kernels/exllama_kernels/cuda_func/column_remap.cu/0
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#include "q_gemm.cuh" #include "util.cuh" #include "matrix_view.cuh" #include "../config.h" #include "quant/qdq_2.cuh" #include "quant/qdq_3.cuh" #include "quant/qdq_4.cuh" #include "quant/qdq_5.cuh" #include "quant/qdq_6.cuh" #include "quant/qdq_8.cuh" #define GPTQ_BLOCK_KN_SIZE 128 #define GPTQ_BLOCK_M_SIZE_MAX 8 #...
text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/q_gemm.cu/0
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# test_watermark_logits_processor.py import os import numpy as np import torch from text_generation_server.utils.watermark import WatermarkLogitsProcessor GAMMA = os.getenv("WATERMARK_GAMMA", 0.5) DELTA = os.getenv("WATERMARK_DELTA", 2.0) def test_seed_rng(): input_ids = [101, 2036, 3731, 102, 2003, 103] p...
text-generation-inference/server/tests/utils/test_watermark.py/0
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import intel_extension_for_pytorch as ipex import torch from text_generation_server.models.flash_causal_lm import BLOCK_SIZE from text_generation_server.layers.attention import Seqlen from typing import Optional SUPPORTS_WINDOWING = False def attention( q, k, v, cu_seqlens, max_s, softmax_sca...
text-generation-inference/server/text_generation_server/layers/attention/ipex.py/0
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import torch from torch import nn from accelerate import init_empty_weights from text_generation_server.utils.import_utils import ( SYSTEM, ) # Monkey patching @classmethod def load_layer_norm(cls, prefix, weights, eps): weight = weights.get_tensor(f"{prefix}.weight") bias = weights.get_tensor(f"{prefix}....
text-generation-inference/server/text_generation_server/layers/layernorm.py/0
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import torch import torch.distributed from torch import nn from transformers.activations import ACT2FN from typing import Optional, List, Tuple from text_generation_server.layers.attention import ( paged_attention, attention, reshape_and_cache, Seqlen, ) from text_generation_server.layers import ( ...
text-generation-inference/server/text_generation_server/models/custom_modeling/flash_qwen2_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 from transformers.configuration_utils import PretrainedConfig from transformers.modeling_outputs import CausalLMOutputWithPast from text_generatio...
text-generation-inference/server/text_generation_server/models/custom_modeling/phi_modeling.py/0
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import asyncio import os import torch import time import signal from grpc import aio from loguru import logger from grpc_reflection.v1alpha import reflection from pathlib import Path from typing import List, Optional from text_generation_server.cache import Cache from text_generation_server.interceptor import Except...
text-generation-inference/server/text_generation_server/server.py/0
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# Origin: https://github.com/predibase/lorax # Path: lorax/server/lorax_server/utils/sgmv.py # License: Apache License Version 2.0, January 2004 import os import warnings from functools import lru_cache from typing import List, Tuple import torch import torch.nn.functional as F try: import punica_kernels ...
text-generation-inference/server/text_generation_server/utils/sgmv.py/0
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import { PaddingDirection, WordPiece, punctuationPreTokenizer, sequencePreTokenizer, whitespacePreTokenizer, Encoding, EncodeOptions, Tokenizer, } from '../../' import { InputSequence } from '../../types' const MOCKS_DIR = __dirname + '/__mocks__' describe('Can modify pretokenizers on the fly', () => ...
tokenizers/bindings/node/lib/bindings/encoding.test.ts/0
{ "file_path": "tokenizers/bindings/node/lib/bindings/encoding.test.ts", "repo_id": "tokenizers", "token_count": 3021 }
262
{ "name": "tokenizers-freebsd-x64", "version": "0.13.4-rc1", "os": [ "freebsd" ], "cpu": [ "x64" ], "main": "tokenizers.freebsd-x64.node", "files": [ "tokenizers.freebsd-x64.node" ], "description": "Tokenizers platform specific bindings", "keywords": [ "napi-rs", "NAPI", "N...
tokenizers/bindings/node/npm/freebsd-x64/package.json/0
{ "file_path": "tokenizers/bindings/node/npm/freebsd-x64/package.json", "repo_id": "tokenizers", "token_count": 272 }
263
{ "name": "tokenizers-win32-x64-msvc", "version": "0.13.4-rc1", "os": [ "win32" ], "cpu": [ "x64" ], "main": "tokenizers.win32-x64-msvc.node", "files": [ "tokenizers.win32-x64-msvc.node" ], "description": "Tokenizers platform specific bindings", "keywords": [ "napi-rs", "NAPI",...
tokenizers/bindings/node/npm/win32-x64-msvc/package.json/0
{ "file_path": "tokenizers/bindings/node/npm/win32-x64-msvc/package.json", "repo_id": "tokenizers", "token_count": 277 }
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use napi::bindgen_prelude::*; use napi_derive::napi; use tokenizers as tk; use tokenizers::Encoding; use crate::encoding::JsEncoding; #[napi] pub fn slice(s: String, begin_index: Option<i32>, end_index: Option<i32>) -> Result<String> { let len = s.chars().count(); let get_index = |x: i32| -> usize { if x >= ...
tokenizers/bindings/node/src/utils.rs/0
{ "file_path": "tokenizers/bindings/node/src/utils.rs", "repo_id": "tokenizers", "token_count": 503 }
265
import argparse import glob from os.path import join from tokenizers import ByteLevelBPETokenizer 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_bytelevel_bpe.py/0
{ "file_path": "tokenizers/bindings/python/examples/train_bytelevel_bpe.py", "repo_id": "tokenizers", "token_count": 521 }
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from .. import normalizers Normalizer = normalizers.Normalizer BertNormalizer = normalizers.BertNormalizer NFD = normalizers.NFD NFKD = normalizers.NFKD NFC = normalizers.NFC NFKC = normalizers.NFKC Sequence = normalizers.Sequence Lowercase = normalizers.Lowercase Prepend = normalizers.Prepend Strip = normalizers.Str...
tokenizers/bindings/python/py_src/tokenizers/normalizers/__init__.py/0
{ "file_path": "tokenizers/bindings/python/py_src/tokenizers/normalizers/__init__.py", "repo_id": "tokenizers", "token_count": 304 }
267
[isort] default_section = FIRSTPARTY ensure_newline_before_comments = True force_grid_wrap = 0 include_trailing_comma = True known_first_party = transformers known_third_party = absl conllu datasets elasticsearch fairseq faiss-cpu fastprogress fire fugashi git h5py matplo...
tokenizers/bindings/python/setup.cfg/0
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268
use pyo3::exceptions; use pyo3::prelude::*; use tk::utils::SysRegex; /// Instantiate a new Regex with the given pattern #[pyclass(module = "tokenizers", name = "Regex")] pub struct PyRegex { pub inner: SysRegex, pub pattern: String, } #[pymethods] impl PyRegex { #[new] #[pyo3(text_signature = "(self, ...
tokenizers/bindings/python/src/utils/regex.rs/0
{ "file_path": "tokenizers/bindings/python/src/utils/regex.rs", "repo_id": "tokenizers", "token_count": 273 }
269
from tokenizers import Tokenizer from ..utils import data_dir, doc_wiki_tokenizer disable_printing = True original_print = print def print(*args, **kwargs): if not disable_printing: original_print(*args, **kwargs) class TestQuicktour: # This method contains everything we don't want to run @sta...
tokenizers/bindings/python/tests/documentation/test_quicktour.py/0
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# Encoding <tokenizerslangcontent> <python> ## Encoding [[autodoc]] tokenizers.Encoding - all - attention_mask - ids - n_sequences - offsets - overflowing - sequence_ids - special_tokens_mask - tokens - type_ids - word_ids - words </python> <rust> The Rust API Reference...
tokenizers/docs/source-doc-builder/api/encoding.mdx/0
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from docutils import nodes import sphinx from sphinx.locale import _ from conf import rust_version logger = sphinx.util.logging.getLogger(__name__) class RustRef: def __call__(self, name, rawtext, text, lineno, inliner, options={}, content=[]): doctype = name.split("_")[1] parts = text.split(":...
tokenizers/docs/source/_ext/rust_doc.py/0
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Tokenizers ==================================================================================================== Fast State-of-the-art tokenizers, optimized for both research and production `🤗 Tokenizers`_ provides an implementation of today's most used tokenizers, with a focus on performance and versatility. These t...
tokenizers/docs/source/index.rst/0
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273
use std::time::{Duration, Instant}; use criterion::black_box; use tokenizers::{ Decoder, EncodeInput, Model, Normalizer, PostProcessor, PreTokenizer, TokenizerImpl, Trainer, }; pub fn iter_bench_encode<M, N, PT, PP, D>( iters: u64, tokenizer: &TokenizerImpl<M, N, PT, PP, D>, lines: &[EncodeInput], ) ...
tokenizers/tokenizers/benches/common/mod.rs/0
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274
Copyright (c) [year] [name] Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicens...
tokenizers/tokenizers/examples/unstable_wasm/www/LICENSE-MIT/0
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use crate::tokenizer::{Decoder, Result}; use serde::{Deserialize, Serialize}; #[derive(Deserialize, Clone, Debug, Serialize)] /// The WordPiece decoder takes care of decoding a list of wordpiece tokens /// back into a readable string. #[serde(tag = "type")] #[non_exhaustive] pub struct WordPiece { /// The prefix ...
tokenizers/tokenizers/src/decoders/wordpiece.rs/0
{ "file_path": "tokenizers/tokenizers/src/decoders/wordpiece.rs", "repo_id": "tokenizers", "token_count": 1275 }
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use super::WordLevel; use crate::utils::parallelism::*; use crate::{AddedToken, Result, Trainer}; use serde::{Deserialize, Serialize}; use std::cmp::Ordering; use std::collections::HashMap; #[non_exhaustive] #[derive(Debug, Clone, Builder, Serialize, Deserialize)] pub struct WordLevelTrainer { /// The minimum freq...
tokenizers/tokenizers/src/models/wordlevel/trainer.rs/0
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277
use serde::{Deserialize, Serialize}; use crate::tokenizer::{PreTokenizedString, PreTokenizer, Result, SplitDelimiterBehavior}; use crate::utils::macro_rules_attribute; #[derive(Clone, Debug, PartialEq, Eq)] /// Pre tokenizes the numbers into single tokens. If individual_digits is set /// to true, then all digits are ...
tokenizers/tokenizers/src/pre_tokenizers/digits.rs/0
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use crate::parallelism::*; use crate::tokenizer::{Offsets, Token}; use crate::utils::padding::PaddingDirection; use crate::utils::truncation::TruncationDirection; use serde::{Deserialize, Serialize}; use std::collections::HashMap; use std::ops::Range; /// Represents the output of a `Tokenizer`. #[derive(Default, Parti...
tokenizers/tokenizers/src/tokenizer/encoding.rs/0
{ "file_path": "tokenizers/tokenizers/src/tokenizer/encoding.rs", "repo_id": "tokenizers", "token_count": 17197 }
279
mod common; use common::*; use tokenizers::tokenizer::AddedToken; #[test] fn add_tokens() { let mut tokenizer = get_empty(); assert_eq!( tokenizer.add_special_tokens(&[ AddedToken::from("<cls>", true), AddedToken::from("<sep>", true) ]), 2 ); assert_eq!...
tokenizers/tokenizers/tests/added_tokens.rs/0
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# Awesome projects built with Transformers This page lists awesome projects built on top of Transformers. Transformers is more than a toolkit to use pretrained models: it's a community of projects built around it and the Hugging Face Hub. We want Transformers to enable developers, researchers, students, professors, en...
transformers/awesome-transformers.md/0
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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 libsndfile1-dev espeak-ng time git g++ cmake pkg-config openssh-client git ENV UV_PYTHON=/usr/local/bin/python RUN pip --no-cache-dir install uv && uv venv && uv pip install --no-cache-dir -U pip setupto...
transformers/docker/torch-jax-light.dockerfile/0
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FROM nvidia/cuda:11.8.0-cudnn8-devel-ubuntu20.04 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"] # The following `ARG` are mainly used to specify the versions explicit...
transformers/docker/transformers-quantization-latest-gpu/Dockerfile/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 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/gguf.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/llm_tutorial.md/0
{ "file_path": "transformers/docs/source/en/llm_tutorial.md", "repo_id": "transformers", "token_count": 4493 }
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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/pipelines.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/beit.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/hubert.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/led.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/mobilebert.md/0
{ "file_path": "transformers/docs/source/en/model_doc/mobilebert.md", "repo_id": "transformers", "token_count": 1548 }
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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/nllb.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/persimmon.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/rag.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/swin.md/0
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<!--⚠️ Note that this file is in Markdown but contain specific syntax for our doc-builder (similar to MDX) that may not be rendered properly in your Markdown viewer. --> # Using pipelines for a webserver <Tip> Creating an inference engine is a complex topic, and the "best" solution will most likely depend on your pr...
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- sections: - local: pipeline_tutorial title: पाइपलाइनों के साथ अनुमान चलाएँ
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<!--- Copyright 2020 The HuggingFace Team. Tutti i diritti riservati. Concesso in licenza in base alla Licenza Apache, Versione 2.0 (la "Licenza"); non è possibile utilizzare questo file se non in conformità con la Licenza. È possibile ottenere una copia della Licenza all'indirizzo http://www.apache.org/licenses/LICE...
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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. --> # 열심히 번역 중입니다. 조금 이따 만나요!
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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 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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#!/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-...
transformers/examples/flax/image-captioning/create_model_from_encoder_decoder_models.py/0
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# Summarization (Seq2Seq model) training examples The following example showcases how to finetune a sequence-to-sequence model for summarization using the JAX/Flax backend. JAX/Flax allows you to trace pure functions and compile them into efficient, fused accelerator code on both GPU and TPU. Models written in JAX/Fl...
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#!/usr/bin/env python # 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. ...
transformers/examples/legacy/run_language_modeling.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_multi_gpu.py/0
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if ! [ -f ./dev.txt ]; then echo "Downloading CONLL2003 dev dataset...." curl -L -o ./dev.txt 'https://github.com/davidsbatista/NER-datasets/raw/master/CONLL2003/valid.txt' fi if ! [ -f ./test.txt ]; then echo "Downloading CONLL2003 test dataset...." curl -L -o ./test.txt 'https://github.com/davidsbatista/NER-...
transformers/examples/legacy/token-classification/run_chunk.sh/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/LI...
transformers/examples/pytorch/language-modeling/run_fim.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 ...
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#!/usr/bin/env python # 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. ...
transformers/examples/pytorch/text-classification/run_xnli.py/0
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<!--- Copyright 2020 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or ...
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# MIT License # Copyright (c) 2019 Yang Liu and the HuggingFace team # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, c...
transformers/examples/research_projects/bertabs/modeling_bertabs.py/0
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import json import multiprocessing import os import re from collections import defaultdict import torch from accelerate import Accelerator from accelerate.utils import set_seed from arguments import HumanEvalArguments from datasets import load_dataset, load_metric from torch.utils.data import IterableDataset from torc...
transformers/examples/research_projects/codeparrot/scripts/human_eval.py/0
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import torch from torch import nn from torch.nn import CrossEntropyLoss, MSELoss from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward from transformers.models.bert.modeling_bert import ( BERT_INPUTS_DOCSTRING, BERT_START_DOCSTRING, BertEmbeddings, BertLayer, ...
transformers/examples/research_projects/deebert/src/modeling_highway_bert.py/0
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#!/usr/bin/env python # coding=utf-8 # Copyright 2022 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LI...
transformers/examples/research_projects/luke/run_luke_ner_no_trainer.py/0
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# Movement Pruning: Adaptive Sparsity by Fine-Tuning Author: @VictorSanh *Magnitude pruning is a widely used strategy for reducing model size in pure supervised learning; however, it is less effective in the transfer learning regime that has become standard for state-of-the-art natural language processing application...
transformers/examples/research_projects/movement-pruning/README.md/0
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<!--- Copyright 2021 NVIDIA Corporation. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agr...
transformers/examples/research_projects/quantization-qdqbert/README.md/0
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import logging import os from typing import List, Tuple import numpy as np import psutil import torch import torch.distributed as dist from transformers import RagRetriever logger = logging.getLogger(__name__) class RagPyTorchDistributedRetriever(RagRetriever): """ A distributed retriever built on top of ...
transformers/examples/research_projects/rag/distributed_pytorch_retriever.py/0
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#!/usr/bin/env python # coding=utf-8 # Copyright 2022 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LI...
transformers/examples/research_projects/robust-speech-event/run_speech_recognition_ctc_streaming.py/0
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#!/usr/bin/env bash export PYTHONPATH="../":"${PYTHONPATH}" export WANDB_PROJECT=dmar export MAX_LEN=128 export m=sshleifer/student_marian_en_ro_6_1 python finetune.py \ --learning_rate=3e-4 \ --do_train \ --fp16 \ --data_dir wmt_en_ro \ --max_source_length $MAX_LEN --max_target_length $MAX_LEN --val_max_targ...
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<!--- Copyright 2022 The Microsoft Inc. 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 re...
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