text stringlengths 7 324k | id stringlengths 14 166 | metadata dict | __index_level_0__ int64 0 463 |
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# SWSL ResNeXt
A **ResNeXt** repeats a [building block](https://paperswithcode.com/method/resnext-block) that aggregates a set of transformations with the same topology. Compared to a [ResNet](https://paperswithcode.com/method/resnet), it exposes a new dimension, *cardinality* (the size of the set of transformations)... | pytorch-image-models/docs/models/.templates/models/swsl-resnext.md/0 | {
"file_path": "pytorch-image-models/docs/models/.templates/models/swsl-resnext.md",
"repo_id": "pytorch-image-models",
"token_count": 2646
} | 180 |
- sections:
- local: index
title: Home
- local: quickstart
title: Quickstart
- local: installation
title: Installation
title: Get started
- sections:
- local: feature_extraction
title: Using Pretrained Models as Feature Extractors
- local: training_script
title: Training With The Offici... | pytorch-image-models/hfdocs/source/_toctree.yml/0 | {
"file_path": "pytorch-image-models/hfdocs/source/_toctree.yml",
"repo_id": "pytorch-image-models",
"token_count": 1686
} | 181 |
# EfficientNet (Knapsack Pruned)
**EfficientNet** is a convolutional neural network architecture and scaling method that uniformly scales all dimensions of depth/width/resolution using a *compound coefficient*. Unlike conventional practice that arbitrary scales these factors, the EfficientNet scaling method uniformly... | pytorch-image-models/hfdocs/source/models/efficientnet-pruned.mdx/0 | {
"file_path": "pytorch-image-models/hfdocs/source/models/efficientnet-pruned.mdx",
"repo_id": "pytorch-image-models",
"token_count": 2777
} | 182 |
# (Legacy) SE-ResNet
**SE ResNet** is a variant of a [ResNet](https://www.paperswithcode.com/method/resnet) that employs [squeeze-and-excitation blocks](https://paperswithcode.com/method/squeeze-and-excitation-block) to enable the network to perform dynamic channel-wise feature recalibration.
## How do I use this mod... | pytorch-image-models/hfdocs/source/models/legacy-se-resnet.mdx/0 | {
"file_path": "pytorch-image-models/hfdocs/source/models/legacy-se-resnet.mdx",
"repo_id": "pytorch-image-models",
"token_count": 3701
} | 183 |
# ResNet
**Residual Networks**, or **ResNets**, learn residual functions with reference to the layer inputs, instead of learning unreferenced functions. Instead of hoping each few stacked layers directly fit a desired underlying mapping, residual nets let these layers fit a residual mapping. They stack [residual block... | pytorch-image-models/hfdocs/source/models/resnet.mdx/0 | {
"file_path": "pytorch-image-models/hfdocs/source/models/resnet.mdx",
"repo_id": "pytorch-image-models",
"token_count": 5074
} | 184 |
# (Tensorflow) MixNet
**MixNet** is a type of convolutional neural network discovered via AutoML that utilises [MixConvs](https://paperswithcode.com/method/mixconv) instead of regular [depthwise convolutions](https://paperswithcode.com/method/depthwise-convolution).
The weights from this model were ported from [Tenso... | pytorch-image-models/hfdocs/source/models/tf-mixnet.mdx/0 | {
"file_path": "pytorch-image-models/hfdocs/source/models/tf-mixnet.mdx",
"repo_id": "pytorch-image-models",
"token_count": 2359
} | 185 |
""" ONNX export script
Export PyTorch models as ONNX graphs.
This export script originally started as an adaptation of code snippets found at
https://pytorch.org/tutorials/advanced/super_resolution_with_onnxruntime.html
The default parameters work with PyTorch 1.6 and ONNX 1.7 and produce an optimal ONNX graph
for h... | pytorch-image-models/onnx_export.py/0 | {
"file_path": "pytorch-image-models/onnx_export.py",
"repo_id": "pytorch-image-models",
"token_count": 1811
} | 186 |
""" Optimzier Tests
These tests were adapted from PyTorch' optimizer tests.
"""
import math
import pytest
import functools
from copy import deepcopy
import torch
from torch.testing._internal.common_utils import TestCase
from torch.nn import Parameter
from timm.scheduler import PlateauLRScheduler
from timm.optim imp... | pytorch-image-models/tests/test_optim.py/0 | {
"file_path": "pytorch-image-models/tests/test_optim.py",
"repo_id": "pytorch-image-models",
"token_count": 11722
} | 187 |
""" Mixup and Cutmix
Papers:
mixup: Beyond Empirical Risk Minimization (https://arxiv.org/abs/1710.09412)
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features (https://arxiv.org/abs/1905.04899)
Code Reference:
CutMix: https://github.com/clovaai/CutMix-PyTorch
Hacked together by / Co... | pytorch-image-models/timm/data/mixup.py/0 | {
"file_path": "pytorch-image-models/timm/data/mixup.py",
"repo_id": "pytorch-image-models",
"token_count": 7225
} | 188 |
""" Tensorflow Preprocessing Adapter
Allows use of Tensorflow preprocessing pipeline in PyTorch Transform
Copyright of original Tensorflow code below.
Hacked together by / Copyright 2020 Ross Wightman
"""
# Copyright 2018 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.... | pytorch-image-models/timm/data/tf_preprocessing.py/0 | {
"file_path": "pytorch-image-models/timm/data/tf_preprocessing.py",
"repo_id": "pytorch-image-models",
"token_count": 3775
} | 189 |
""" Conv2d w/ Same Padding
Hacked together by / Copyright 2020 Ross Wightman
"""
import torch
import torch.nn as nn
import torch.nn.functional as F
from typing import Tuple, Optional
from .config import is_exportable, is_scriptable
from .padding import pad_same, pad_same_arg, get_padding_value
_USE_EXPORT_CONV = Fa... | pytorch-image-models/timm/layers/conv2d_same.py/0 | {
"file_path": "pytorch-image-models/timm/layers/conv2d_same.py",
"repo_id": "pytorch-image-models",
"token_count": 1560
} | 190 |
""" Global Response Normalization Module
Based on the GRN layer presented in
`ConvNeXt-V2 - Co-designing and Scaling ConvNets with Masked Autoencoders` - https://arxiv.org/abs/2301.00808
This implementation
* works for both NCHW and NHWC tensor layouts
* uses affine param names matching existing torch norm layers
* s... | pytorch-image-models/timm/layers/grn.py/0 | {
"file_path": "pytorch-image-models/timm/layers/grn.py",
"repo_id": "pytorch-image-models",
"token_count": 565
} | 191 |
""" Image to Patch Embedding using Conv2d
A convolution based approach to patchifying a 2D image w/ embedding projection.
Based on code in:
* https://github.com/google-research/vision_transformer
* https://github.com/google-research/big_vision/tree/main/big_vision
Hacked together by / Copyright 2020 Ross Wightma... | pytorch-image-models/timm/layers/patch_embed.py/0 | {
"file_path": "pytorch-image-models/timm/layers/patch_embed.py",
"repo_id": "pytorch-image-models",
"token_count": 4705
} | 192 |
from .asymmetric_loss import AsymmetricLossMultiLabel, AsymmetricLossSingleLabel
from .binary_cross_entropy import BinaryCrossEntropy
from .cross_entropy import LabelSmoothingCrossEntropy, SoftTargetCrossEntropy
from .jsd import JsdCrossEntropy
| pytorch-image-models/timm/loss/__init__.py/0 | {
"file_path": "pytorch-image-models/timm/loss/__init__.py",
"repo_id": "pytorch-image-models",
"token_count": 70
} | 193 |
import os
import pkgutil
from copy import deepcopy
from torch import nn as nn
from timm.layers import Conv2dSame, BatchNormAct2d, Linear
__all__ = ['extract_layer', 'set_layer', 'adapt_model_from_string', 'adapt_model_from_file']
def extract_layer(model, layer):
layer = layer.split('.')
module = model
... | pytorch-image-models/timm/models/_prune.py/0 | {
"file_path": "pytorch-image-models/timm/models/_prune.py",
"repo_id": "pytorch-image-models",
"token_count": 2021
} | 194 |
"""PyTorch CspNet
A PyTorch implementation of Cross Stage Partial Networks including:
* CSPResNet50
* CSPResNeXt50
* CSPDarkNet53
* and DarkNet53 for good measure
Based on paper `CSPNet: A New Backbone that can Enhance Learning Capability of CNN` - https://arxiv.org/abs/1911.11929
Reference impl via darknet cfg file... | pytorch-image-models/timm/models/cspnet.py/0 | {
"file_path": "pytorch-image-models/timm/models/cspnet.py",
"repo_id": "pytorch-image-models",
"token_count": 19954
} | 195 |
""" FocalNet
As described in `Focal Modulation Networks` - https://arxiv.org/abs/2203.11926
Significant modifications and refactoring from the original impl at https://github.com/microsoft/FocalNet
This impl is/has:
* fully convolutional, NCHW tensor layout throughout, seemed to have minimal performance impact but m... | pytorch-image-models/timm/models/focalnet.py/0 | {
"file_path": "pytorch-image-models/timm/models/focalnet.py",
"repo_id": "pytorch-image-models",
"token_count": 11585
} | 196 |
"""
Poolformer from MetaFormer is Actually What You Need for Vision https://arxiv.org/abs/2111.11418
IdentityFormer, RandFormer, PoolFormerV2, ConvFormer, and CAFormer
from MetaFormer Baselines for Vision https://arxiv.org/abs/2210.13452
All implemented models support feature extraction and variable input resolution.... | pytorch-image-models/timm/models/metaformer.py/0 | {
"file_path": "pytorch-image-models/timm/models/metaformer.py",
"repo_id": "pytorch-image-models",
"token_count": 17521
} | 197 |
""" Res2Net and Res2NeXt
Adapted from Official Pytorch impl at: https://github.com/gasvn/Res2Net/
Paper: `Res2Net: A New Multi-scale Backbone Architecture` - https://arxiv.org/abs/1904.01169
"""
import math
import torch
import torch.nn as nn
from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
from ._bui... | pytorch-image-models/timm/models/res2net.py/0 | {
"file_path": "pytorch-image-models/timm/models/res2net.py",
"repo_id": "pytorch-image-models",
"token_count": 3659
} | 198 |
"""VGG
Adapted from https://github.com/pytorch/vision 'vgg.py' (BSD-3-Clause) with a few changes for
timm functionality.
Copyright 2021 Ross Wightman
"""
from typing import Union, List, Dict, Any, cast
import torch
import torch.nn as nn
import torch.nn.functional as F
from timm.data import IMAGENET_DEFAULT_MEAN, IM... | pytorch-image-models/timm/models/vgg.py/0 | {
"file_path": "pytorch-image-models/timm/models/vgg.py",
"repo_id": "pytorch-image-models",
"token_count": 5201
} | 199 |
""" AdamW Optimizer
Impl copied from PyTorch master
NOTE: Builtin optim.AdamW is used by the factory, this impl only serves as a Python based reference, will be removed
someday
"""
import math
import torch
from torch.optim.optimizer import Optimizer
class AdamW(Optimizer):
r"""Implements AdamW algorithm.
Th... | pytorch-image-models/timm/optim/adamw.py/0 | {
"file_path": "pytorch-image-models/timm/optim/adamw.py",
"repo_id": "pytorch-image-models",
"token_count": 2417
} | 200 |
""" Cosine Scheduler
Cosine LR schedule with warmup, cycle/restarts, noise, k-decay.
Hacked together by / Copyright 2021 Ross Wightman
"""
import logging
import math
import numpy as np
import torch
from .scheduler import Scheduler
_logger = logging.getLogger(__name__)
class CosineLRScheduler(Scheduler):
"""
... | pytorch-image-models/timm/scheduler/cosine_lr.py/0 | {
"file_path": "pytorch-image-models/timm/scheduler/cosine_lr.py",
"repo_id": "pytorch-image-models",
"token_count": 2031
} | 201 |
""" Logging helpers
Hacked together by / Copyright 2020 Ross Wightman
"""
import logging
import logging.handlers
class FormatterNoInfo(logging.Formatter):
def __init__(self, fmt='%(levelname)s: %(message)s'):
logging.Formatter.__init__(self, fmt)
def format(self, record):
if record.levelno =... | pytorch-image-models/timm/utils/log.py/0 | {
"file_path": "pytorch-image-models/timm/utils/log.py",
"repo_id": "pytorch-image-models",
"token_count": 383
} | 202 |
import pytest
from text_generation import __version__
from huggingface_hub.utils import build_hf_headers
@pytest.fixture
def flan_t5_xxl():
return "google/flan-t5-xxl"
@pytest.fixture
def fake_model():
return "fake/model"
@pytest.fixture
def unsupported_model():
return "gpt2"
@pytest.fixture
def ba... | text-generation-inference/clients/python/tests/conftest.py/0 | {
"file_path": "text-generation-inference/clients/python/tests/conftest.py",
"repo_id": "text-generation-inference",
"token_count": 390
} | 203 |
# Non-core Model Serving
TGI supports various LLM architectures (see full list [here](../supported_models)). If you wish to serve a model that is not one of the supported models, TGI will fallback to the `transformers` implementation of that model. This means you will be unable to use some of the features introduced b... | text-generation-inference/docs/source/basic_tutorials/non_core_models.md/0 | {
"file_path": "text-generation-inference/docs/source/basic_tutorials/non_core_models.md",
"repo_id": "text-generation-inference",
"token_count": 472
} | 204 |
import sys
import subprocess
import contextlib
import pytest
import asyncio
import os
import docker
import json
import math
import time
import random
from docker.errors import NotFound
from typing import Optional, List, Dict
from syrupy.extensions.json import JSONSnapshotExtension
from aiohttp import ClientConnectorEr... | text-generation-inference/integration-tests/conftest.py/0 | {
"file_path": "text-generation-inference/integration-tests/conftest.py",
"repo_id": "text-generation-inference",
"token_count": 7278
} | 205 |
[
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [
{
"id": 2,
"logprob": null,
"text": "<bos>"
},
{
"id": 2015,
"logprob": -10.0,
"text": "Test"
... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_gemma/test_flash_gemma_load.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_gemma/test_flash_gemma_load.json",
"repo_id": "text-generation-inference",
"token_count": 4916
} | 206 |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [
{
"id": 1,
"logprob": null,
"text": "<s>"
},
{
"id": 3735,
"logprob": -12.9140625,
"text": "Test"
},
{
"id": 2... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_mistral/test_flash_mistral_all_params.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_mistral/test_flash_mistral_all_params.json",
"repo_id": "text-generation-inference",
"token_count": 1041
} | 207 |
[
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [
{
"id": 589,
"logprob": null,
"text": "def"
},
{
"id": 1459,
"logprob": -5.6289062,
"text": " prin... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_starcoder/test_flash_starcoder_load.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_starcoder/test_flash_starcoder_load.json",
"repo_id": "text-generation-inference",
"token_count": 5176
} | 208 |
{
"details": {
"best_of_sequences": null,
"finish_reason": "eos_token",
"generated_tokens": 9,
"prefill": [
{
"id": 0,
"logprob": null,
"text": "<pad>"
}
],
"seed": 0,
"tokens": [
{
"id": 16017,
"logprob": -0.30908203,
"spec... | text-generation-inference/integration-tests/models/__snapshots__/test_mt0_base/test_mt0_base_all_params.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_mt0_base/test_mt0_base_all_params.json",
"repo_id": "text-generation-inference",
"token_count": 831
} | 209 |
import pytest
@pytest.fixture(scope="module")
def flash_llama_awq_handle_sharded(launcher):
with launcher(
"abhinavkulkarni/codellama-CodeLlama-7b-Python-hf-w4-g128-awq",
num_shard=2,
quantize="awq",
) as handle:
yield handle
@pytest.fixture(scope="module")
async def flash_ll... | text-generation-inference/integration-tests/models/test_flash_awq_sharded.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_flash_awq_sharded.py",
"repo_id": "text-generation-inference",
"token_count": 608
} | 210 |
import pytest
import json
from text_generation.types import GrammarType
@pytest.fixture(scope="module")
def non_flash_llama_grammar_handle(launcher):
with launcher(
"TinyLlama/TinyLlama-1.1B-Chat-v1.0",
num_shard=1,
disable_grammar_support=False,
use_flash_attention=False,
) a... | text-generation-inference/integration-tests/models/test_grammar_llama.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_grammar_llama.py",
"repo_id": "text-generation-inference",
"token_count": 1338
} | 211 |
use clap::{Parser, ValueEnum};
use nix::sys::signal::{self, Signal};
use nix::unistd::Pid;
use serde::Deserialize;
use std::env;
use std::ffi::OsString;
use std::io::{BufRead, BufReader, Lines};
use std::os::unix::process::{CommandExt, ExitStatusExt};
use std::path::Path;
use std::process::{Child, Command, ExitStatus, ... | text-generation-inference/launcher/src/main.rs/0 | {
"file_path": "text-generation-inference/launcher/src/main.rs",
"repo_id": "text-generation-inference",
"token_count": 19919
} | 212 |
//! A crate to extract and inject a OpenTelemetry context from and to a gRPC request.
//! Inspired by: https://github.com/open-telemetry/opentelemetry-rust gRPC examples
use opentelemetry::global;
use opentelemetry::propagation::{Extractor, Injector};
use tracing_opentelemetry::OpenTelemetrySpanExt;
/// Extract conte... | text-generation-inference/router/grpc-metadata/src/lib.rs/0 | {
"file_path": "text-generation-inference/router/grpc-metadata/src/lib.rs",
"repo_id": "text-generation-inference",
"token_count": 889
} | 213 |
selective_scan_commit := 2a3704fd47ba817b415627b06fd796b971fdc137
causal-conv1d:
rm -rf causal-conv1d
git clone https://github.com/Dao-AILab/causal-conv1d.git
build-causal-conv1d: causal-conv1d
cd causal-conv1d/ && git checkout v1.1.1 # known latest working version tag
cd causal-conv1d/ && CAUSAL_CONV1D_FORCE_BUI... | text-generation-inference/server/Makefile-selective-scan/0 | {
"file_path": "text-generation-inference/server/Makefile-selective-scan",
"repo_id": "text-generation-inference",
"token_count": 351
} | 214 |
// Adapted from turboderp exllama: https://github.com/turboderp/exllama
#ifndef _hip_compat_cuh
#define _hip_compat_cuh
// Workaround for a bug in hipamd, backported from upstream, this is fixed in ROCm 5.6.
__device__ __forceinline__ __half __compat_hrcp(__half x) {
return __half_raw{
static_cast<_Float1... | text-generation-inference/server/exllama_kernels/exllama_kernels/hip_compat.cuh/0 | {
"file_path": "text-generation-inference/server/exllama_kernels/exllama_kernels/hip_compat.cuh",
"repo_id": "text-generation-inference",
"token_count": 1708
} | 215 |
#ifndef _qdq_3_cuh
#define _qdq_3_cuh
#include "qdq_util.cuh"
#include "../../config.h"
#if QMODE_3BIT == 1
// Permutation:
//
// v9997775 55333111 u8886664 44222000 (u, v lsb)
// vjjjhhhf ffdddbbb uiiiggge eecccaaa
// vtttrrrp ppnnnlll usssqqqo oommmkkk
__forceinline__ __device__ void shuffle_3bit_32
(
uin... | text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/quant/qdq_3.cuh/0 | {
"file_path": "text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/quant/qdq_3.cuh",
"repo_id": "text-generation-inference",
"token_count": 3335
} | 216 |
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.causal_lm import CausalLM, CausalLMBatch
@pytest.fixture(scope="session")
def default_causal_lm():
return CausalLM("gpt2")
@pytest.fixtu... | text-generation-inference/server/tests/models/test_causal_lm.py/0 | {
"file_path": "text-generation-inference/server/tests/models/test_causal_lm.py",
"repo_id": "text-generation-inference",
"token_count": 5345
} | 217 |
# This code was adapted from https://github.com/lucidrains/flamingo-pytorch licensed under the MIT License.
#
# MIT License
#
# Copyright (c) 2020 The Google AI Language Team Authors, The HuggingFace Inc. team and github/lonePatient
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of ... | text-generation-inference/server/text_generation_server/models/custom_modeling/idefics_perceiver.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/models/custom_modeling/idefics_perceiver.py",
"repo_id": "text-generation-inference",
"token_count": 5171
} | 218 |
import math
import torch
import torch.distributed
from opentelemetry import trace
from transformers.models.qwen2 import Qwen2Tokenizer
from typing import Optional
from text_generation_server.models.cache_manager import BLOCK_SIZE
from text_generation_server.models.flash_mistral import (
BaseFlashMistral,
set... | text-generation-inference/server/text_generation_server/models/flash_qwen2.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/models/flash_qwen2.py",
"repo_id": "text-generation-inference",
"token_count": 1259
} | 219 |
import torch
import time
from dataclasses import dataclass
from opentelemetry import trace
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, PreTrainedTokenizerBase
from typing import Optional, Tuple, List, Type, Dict
from text_generation_server.utils.tokens import batch_top_tokens
from text_generation_s... | text-generation-inference/server/text_generation_server/models/seq2seq_lm.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/models/seq2seq_lm.py",
"repo_id": "text-generation-inference",
"token_count": 16433
} | 220 |
import time
import torch.nn as nn
import math
import json
import os
import torch
import transformers
from texttable import Texttable
from transformers import AutoModelForCausalLM, AutoConfig, AutoTokenizer
from huggingface_hub import HfApi
from accelerate import init_empty_weights
from text_generation_server.utils imp... | text-generation-inference/server/text_generation_server/utils/gptq/quantize.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/utils/gptq/quantize.py",
"repo_id": "text-generation-inference",
"token_count": 15970
} | 221 |
# EditorConfig helps developers define and maintain consistent
# coding styles between different editors or IDEs
# http://editorconfig.org
root = true
[*]
indent_style = space
indent_size = 2
end_of_line = lf
charset = utf-8
trim_trailing_whitespace = true
insert_final_newline = true
[*.md]
trim_trailing_whitespace =... | tokenizers/bindings/node/.editorconfig/0 | {
"file_path": "tokenizers/bindings/node/.editorconfig",
"repo_id": "tokenizers",
"token_count": 108
} | 222 |
/* tslint:disable */
/* eslint-disable */
/* prettier-ignore */
/* auto-generated by NAPI-RS */
const { existsSync, readFileSync } = require('fs')
const { join } = require('path')
const { platform, arch } = process
let nativeBinding = null
let localFileExisted = false
let loadError = null
function isMusl() {
// ... | tokenizers/bindings/node/index.js/0 | {
"file_path": "tokenizers/bindings/node/index.js",
"repo_id": "tokenizers",
"token_count": 4683
} | 223 |
{
"name": "tokenizers-android-arm64",
"version": "0.13.4-rc1",
"os": [
"android"
],
"cpu": [
"arm64"
],
"main": "tokenizers.android-arm64.node",
"files": [
"tokenizers.android-arm64.node"
],
"description": "Tokenizers platform specific bindings",
"keywords": [
"napi-rs",
"NAPI"... | tokenizers/bindings/node/npm/android-arm64/package.json/0 | {
"file_path": "tokenizers/bindings/node/npm/android-arm64/package.json",
"repo_id": "tokenizers",
"token_count": 264
} | 224 |
{
"name": "tokenizers-linux-x64-musl",
"version": "0.13.4-rc1",
"os": [
"linux"
],
"cpu": [
"x64"
],
"main": "tokenizers.linux-x64-musl.node",
"files": [
"tokenizers.linux-x64-musl.node"
],
"description": "Tokenizers platform specific bindings",
"keywords": [
"napi-rs",
"NAPI",... | tokenizers/bindings/node/npm/linux-x64-musl/package.json/0 | {
"file_path": "tokenizers/bindings/node/npm/linux-x64-musl/package.json",
"repo_id": "tokenizers",
"token_count": 291
} | 225 |
use crate::arc_rwlock_serde;
use serde::{Deserialize, Serialize};
extern crate tokenizers as tk;
use napi::bindgen_prelude::*;
use napi_derive::napi;
use std::sync::{Arc, RwLock};
use tk::processors::PostProcessorWrapper;
use tk::Encoding;
#[derive(Clone, Serialize, Deserialize)]
#[napi]
pub struct Processor {
#[se... | tokenizers/bindings/node/src/processors.rs/0 | {
"file_path": "tokenizers/bindings/node/src/processors.rs",
"repo_id": "tokenizers",
"token_count": 1336
} | 226 |
<p align="center">
<br>
<img src="https://huggingface.co/landing/assets/tokenizers/tokenizers-logo.png" width="600"/>
<br>
<p>
<p align="center">
<a href="https://badge.fury.io/py/tokenizers">
<img alt="Build" src="https://badge.fury.io/py/tokenizers.svg">
</a>
<a href="https://github.c... | tokenizers/bindings/python/README.md/0 | {
"file_path": "tokenizers/bindings/python/README.md",
"repo_id": "tokenizers",
"token_count": 1621
} | 227 |
from typing import Dict, Iterator, List, Optional, Tuple, Union
from .. import AddedToken, Tokenizer, decoders, pre_tokenizers, trainers
from ..models import BPE
from ..normalizers import BertNormalizer, Lowercase, Sequence, unicode_normalizer_from_str
from .base_tokenizer import BaseTokenizer
class CharBPETokenizer... | tokenizers/bindings/python/py_src/tokenizers/implementations/char_level_bpe.py/0 | {
"file_path": "tokenizers/bindings/python/py_src/tokenizers/implementations/char_level_bpe.py",
"repo_id": "tokenizers",
"token_count": 2509
} | 228 |
[project]
name = 'tokenizers'
requires-python = '>=3.7'
authors = [
{name = 'Nicolas Patry', email = 'patry.nicolas@protonmail.com'},
{name = 'Anthony Moi', email = 'anthony@huggingface.co'}
]
classifiers = [
"Development Status :: 5 - Production/Stable",
"Intended Audience :: Developers",
"Intended Audie... | tokenizers/bindings/python/pyproject.toml/0 | {
"file_path": "tokenizers/bindings/python/pyproject.toml",
"repo_id": "tokenizers",
"token_count": 711
} | 229 |
use std::sync::{Arc, RwLock};
use crate::models::PyModel;
use crate::tokenizer::PyAddedToken;
use crate::utils::PyChar;
use pyo3::exceptions;
use pyo3::prelude::*;
use pyo3::types::*;
use serde::{Deserialize, Serialize};
use tk::models::TrainerWrapper;
use tk::Trainer;
use tokenizers as tk;
/// Base class for all tra... | tokenizers/bindings/python/src/trainers.rs/0 | {
"file_path": "tokenizers/bindings/python/src/trainers.rs",
"repo_id": "tokenizers",
"token_count": 17617
} | 230 |
import pickle
import numpy as np
import pytest
from tokenizers import AddedToken, Encoding, Tokenizer
from tokenizers.implementations import BertWordPieceTokenizer
from tokenizers.models import BPE, Model, Unigram
from tokenizers.pre_tokenizers import ByteLevel
from tokenizers.processors import RobertaProcessing
fro... | tokenizers/bindings/python/tests/bindings/test_tokenizer.py/0 | {
"file_path": "tokenizers/bindings/python/tests/bindings/test_tokenizer.py",
"repo_id": "tokenizers",
"token_count": 8966
} | 231 |
- sections:
- local: index
title: 🤗 Tokenizers
- local: quicktour
title: Quicktour
- local: installation
title: Installation
- local: pipeline
title: The tokenization pipeline
- local: components
title: Components
- local: training_from_memory
title: Training from memory
title: G... | tokenizers/docs/source-doc-builder/_toctree.yml/0 | {
"file_path": "tokenizers/docs/source-doc-builder/_toctree.yml",
"repo_id": "tokenizers",
"token_count": 338
} | 232 |
# The tokenization pipeline
When calling `Tokenizer.encode` or
`Tokenizer.encode_batch`, the input
text(s) go through the following pipeline:
- `normalization`
- `pre-tokenization`
- `model`
- `post-processing`
We'll see in details what happens during each of those steps in detail,
as well as when you want t... | tokenizers/docs/source-doc-builder/pipeline.mdx/0 | {
"file_path": "tokenizers/docs/source-doc-builder/pipeline.mdx",
"repo_id": "tokenizers",
"token_count": 5903
} | 233 |
Documentation
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The Rust API Reference is available directly on the `Docs.rs <https://docs.rs/tokenizers>`__
website.
| tokenizers/docs/source/api/rust.inc/0 | {
"file_path": "tokenizers/docs/source/api/rust.inc",
"repo_id": "tokenizers",
"token_count": 43
} | 234 |
<p align="center">
<br>
<img src="https://huggingface.co/landing/assets/tokenizers/tokenizers-logo.png" width="600"/>
<br>
<p>
<p align="center">
<img alt="Build" src="https://github.com/huggingface/tokenizers/workflows/Rust/badge.svg">
<a href="https://github.com/huggingface/tokenizers/blob/master/... | tokenizers/tokenizers/README.md/0 | {
"file_path": "tokenizers/tokenizers/README.md",
"repo_id": "tokenizers",
"token_count": 1846
} | 235 |
language: node_js
node_js: "10"
script:
- ./node_modules/.bin/webpack
| tokenizers/tokenizers/examples/unstable_wasm/www/.travis.yml/0 | {
"file_path": "tokenizers/tokenizers/examples/unstable_wasm/www/.travis.yml",
"repo_id": "tokenizers",
"token_count": 30
} | 236 |
use crate::decoders::DecoderWrapper;
use crate::tokenizer::{Decoder, Result};
use crate::utils::macro_rules_attribute;
use serde::{Deserialize, Serialize};
#[derive(Clone, Debug)]
#[macro_rules_attribute(impl_serde_type!)]
pub struct Sequence {
decoders: Vec<DecoderWrapper>,
}
impl Sequence {
pub fn new(decod... | tokenizers/tokenizers/src/decoders/sequence.rs/0 | {
"file_path": "tokenizers/tokenizers/src/decoders/sequence.rs",
"repo_id": "tokenizers",
"token_count": 600
} | 237 |
use super::OrderedVocabIter;
use crate::tokenizer::{Model, Result, Token};
use serde_json::Value;
use std::collections::HashMap;
use std::fs::File;
use std::io::{BufReader, Read, Write};
use std::path::{Path, PathBuf};
mod serialization;
mod trainer;
// Re-export
pub use trainer::*;
type Vocab = HashMap<String, u32>... | tokenizers/tokenizers/src/models/wordlevel/mod.rs/0 | {
"file_path": "tokenizers/tokenizers/src/models/wordlevel/mod.rs",
"repo_id": "tokenizers",
"token_count": 3383
} | 238 |
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
} | 239 |
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": 16897
} | 240 |
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
} | 241 |
FROM google/cloud-sdk:slim
# Build args.
ARG GITHUB_REF=refs/heads/main
# TODO: This Dockerfile installs pytorch/xla 3.6 wheels. There are also 3.7
# wheels available; see below.
ENV PYTHON_VERSION=3.6
RUN apt-get update && apt-get install -y --no-install-recommends \
build-essential \
cmake \
... | transformers/docker/transformers-pytorch-tpu/Dockerfile/0 | {
"file_path": "transformers/docker/transformers-pytorch-tpu/Dockerfile",
"repo_id": "transformers",
"token_count": 1235
} | 242 |
<!---
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 ... | transformers/docs/source/de/contributing.md/0 | {
"file_path": "transformers/docs/source/de/contributing.md",
"repo_id": "transformers",
"token_count": 8257
} | 243 |
- sections:
- local: index
title: 🤗 Transformers
- local: quicktour
title: Quick tour
- local: installation
title: Installation
title: Get started
- sections:
- local: pipeline_tutorial
title: Run inference with pipelines
- local: autoclass_tutorial
title: Write portable code with AutoC... | transformers/docs/source/en/_toctree.yml/0 | {
"file_path": "transformers/docs/source/en/_toctree.yml",
"repo_id": "transformers",
"token_count": 11006
} | 244 |
<!--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/debugging.md/0 | {
"file_path": "transformers/docs/source/en/debugging.md",
"repo_id": "transformers",
"token_count": 6482
} | 245 |
<!--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/onnx.md/0 | {
"file_path": "transformers/docs/source/en/main_classes/onnx.md",
"repo_id": "transformers",
"token_count": 523
} | 246 |
<!--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/bart.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/bart.md",
"repo_id": "transformers",
"token_count": 3297
} | 247 |
<!--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/bloom.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/bloom.md",
"repo_id": "transformers",
"token_count": 1158
} | 248 |
<!--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
} | 249 |
<!--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/dialogpt.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/dialogpt.md",
"repo_id": "transformers",
"token_count": 789
} | 250 |
<!--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/falcon.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/falcon.md",
"repo_id": "transformers",
"token_count": 837
} | 251 |
<!--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/madlad-400.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/madlad-400.md",
"repo_id": "transformers",
"token_count": 930
} | 252 |
<!--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
} | 253 |
<!--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/nougat.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/nougat.md",
"repo_id": "transformers",
"token_count": 1549
} | 254 |
<!--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/roberta-prelayernorm.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/roberta-prelayernorm.md",
"repo_id": "transformers",
"token_count": 1519
} | 255 |
<!--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/wavlm.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/wavlm.md",
"repo_id": "transformers",
"token_count": 972
} | 256 |
<!--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_sharing.md/0 | {
"file_path": "transformers/docs/source/en/model_sharing.md",
"repo_id": "transformers",
"token_count": 2967
} | 257 |
<!---
Copyright 2021 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or ... | transformers/docs/source/en/performance.md/0 | {
"file_path": "transformers/docs/source/en/performance.md",
"repo_id": "transformers",
"token_count": 966
} | 258 |
<!--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/tasks/idefics.md/0 | {
"file_path": "transformers/docs/source/en/tasks/idefics.md",
"repo_id": "transformers",
"token_count": 6890
} | 259 |
<!--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/transformers_agents.md/0 | {
"file_path": "transformers/docs/source/en/transformers_agents.md",
"repo_id": "transformers",
"token_count": 4397
} | 260 |
<!--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/es/tasks/asr.md/0 | {
"file_path": "transformers/docs/source/es/tasks/asr.md",
"repo_id": "transformers",
"token_count": 6032
} | 261 |
<!---
Copyright 2022 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or ... | transformers/docs/source/fr/installation.md/0 | {
"file_path": "transformers/docs/source/fr/installation.md",
"repo_id": "transformers",
"token_count": 3849
} | 262 |
<!--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/it/preprocessing.md/0 | {
"file_path": "transformers/docs/source/it/preprocessing.md",
"repo_id": "transformers",
"token_count": 9562
} | 263 |
<!--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/ja/create_a_model.md/0 | {
"file_path": "transformers/docs/source/ja/create_a_model.md",
"repo_id": "transformers",
"token_count": 8236
} | 264 |
<!--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/ja/model_doc/beit.md/0 | {
"file_path": "transformers/docs/source/ja/model_doc/beit.md",
"repo_id": "transformers",
"token_count": 3840
} | 265 |
<!--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/ja/model_doc/bros.md/0 | {
"file_path": "transformers/docs/source/ja/model_doc/bros.md",
"repo_id": "transformers",
"token_count": 3458
} | 266 |
<!--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/ja/model_summary.md/0 | {
"file_path": "transformers/docs/source/ja/model_summary.md",
"repo_id": "transformers",
"token_count": 9488
} | 267 |
<!--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/ja/perf_train_tpu_tf.md/0 | {
"file_path": "transformers/docs/source/ja/perf_train_tpu_tf.md",
"repo_id": "transformers",
"token_count": 7360
} | 268 |
<!--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/ja/tasks/image_captioning.md/0 | {
"file_path": "transformers/docs/source/ja/tasks/image_captioning.md",
"repo_id": "transformers",
"token_count": 3779
} | 269 |
<!--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/ja/tasks/translation.md/0 | {
"file_path": "transformers/docs/source/ja/tasks/translation.md",
"repo_id": "transformers",
"token_count": 7463
} | 270 |
<!--Copyright 2022 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | transformers/docs/source/ko/accelerate.md/0 | {
"file_path": "transformers/docs/source/ko/accelerate.md",
"repo_id": "transformers",
"token_count": 2885
} | 271 |
<!--Copyright 2022 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | transformers/docs/source/ko/hpo_train.md/0 | {
"file_path": "transformers/docs/source/ko/hpo_train.md",
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<!--Copyright 2020 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | transformers/docs/source/ko/serialization.md/0 | {
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"repo_id": "transformers",
"token_count": 6886
} | 273 |
<!--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/pt/tasks/token_classification.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
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#!/usr/bin/env python
# coding=utf-8
# Copyright 2021 The HuggingFace Team All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-... | transformers/examples/flax/language-modeling/run_clm_flax.py/0 | {
"file_path": "transformers/examples/flax/language-modeling/run_clm_flax.py",
"repo_id": "transformers",
"token_count": 16207
} | 276 |
# 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/rouge_cli.py/0 | {
"file_path": "transformers/examples/legacy/seq2seq/rouge_cli.py",
"repo_id": "transformers",
"token_count": 385
} | 277 |
# coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a cop... | transformers/examples/legacy/token-classification/utils_ner.py/0 | {
"file_path": "transformers/examples/legacy/token-classification/utils_ner.py",
"repo_id": "transformers",
"token_count": 7660
} | 278 |
#!/usr/bin/env python
# coding=utf-8
# Copyright 2022 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LI... | transformers/examples/pytorch/image-pretraining/run_mae.py/0 | {
"file_path": "transformers/examples/pytorch/image-pretraining/run_mae.py",
"repo_id": "transformers",
"token_count": 6396
} | 279 |
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