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# ResNeSt
A **ResNeSt** is a variant on a [ResNet](https://paperswithcode.com/method/resnet), which instead stacks [Split-Attention blocks](https://paperswithcode.com/method/split-attention). The cardinal group representations are then concatenated along the channel dimension: $V = \text{Concat}${$V^{1},V^{2},\cdots{V... | pytorch-image-models/docs/models/.templates/models/resnest.md/0 | {
"file_path": "pytorch-image-models/docs/models/.templates/models/resnest.md",
"repo_id": "pytorch-image-models",
"token_count": 4643
} | 157 |
# (Tensorflow) EfficientNet Lite
**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/docs/models/.templates/models/tf-efficientnet-lite.md/0 | {
"file_path": "pytorch-image-models/docs/models/.templates/models/tf-efficientnet-lite.md",
"repo_id": "pytorch-image-models",
"token_count": 2543
} | 158 |
# Sharing and Loading Models From the Hugging Face Hub
The `timm` library has a built-in integration with the Hugging Face Hub, making it easy to share and load models from the 🤗 Hub.
In this short guide, we'll see how to:
1. Share a `timm` model on the Hub
2. How to load that model back from the Hub
## Authent... | pytorch-image-models/hfdocs/source/hf_hub.mdx/0 | {
"file_path": "pytorch-image-models/hfdocs/source/hf_hub.mdx",
"repo_id": "pytorch-image-models",
"token_count": 594
} | 159 |
[tool.pytest.ini_options]
markers = [
"base: marker for model tests using the basic setup",
"cfg: marker for model tests checking the config",
"torchscript: marker for model tests using torchscript",
"features: marker for model tests checking feature extraction",
"fxforward: marker for model tests u... | pytorch-image-models/pyproject.toml/0 | {
"file_path": "pytorch-image-models/pyproject.toml",
"repo_id": "pytorch-image-models",
"token_count": 169
} | 160 |
""" 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
} | 161 |
""" 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
} | 162 |
""" 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
} | 163 |
""" 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
} | 164 |
""" 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
} | 165 |
""" 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
} | 166 |
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
} | 167 |
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
} | 168 |
"""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
} | 169 |
""" 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
} | 170 |
""" MLP-Mixer, ResMLP, and gMLP in PyTorch
This impl originally based on MLP-Mixer paper.
Official JAX impl: https://github.com/google-research/vision_transformer/blob/linen/vit_jax/models_mixer.py
Paper: 'MLP-Mixer: An all-MLP Architecture for Vision' - https://arxiv.org/abs/2105.01601
@article{tolstikhin2021,
t... | pytorch-image-models/timm/models/mlp_mixer.py/0 | {
"file_path": "pytorch-image-models/timm/models/mlp_mixer.py",
"repo_id": "pytorch-image-models",
"token_count": 11661
} | 171 |
"""PyTorch ResNet
This started as a copy of https://github.com/pytorch/vision 'resnet.py' (BSD-3-Clause) with
additional dropout and dynamic global avg/max pool.
ResNeXt, SE-ResNeXt, SENet, and MXNet Gluon stem/downsample variants, tiered stems added by Ross Wightman
Copyright 2019, Ross Wightman
"""
import math
fro... | pytorch-image-models/timm/models/resnet.py/0 | {
"file_path": "pytorch-image-models/timm/models/resnet.py",
"repo_id": "pytorch-image-models",
"token_count": 44237
} | 172 |
""" Vision Transformer (ViT) in PyTorch
A PyTorch implement of Vision Transformers as described in:
'An Image Is Worth 16 x 16 Words: Transformers for Image Recognition at Scale'
- https://arxiv.org/abs/2010.11929
`How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers`
- https:... | pytorch-image-models/timm/models/vision_transformer.py/0 | {
"file_path": "pytorch-image-models/timm/models/vision_transformer.py",
"repo_id": "pytorch-image-models",
"token_count": 57595
} | 173 |
""" PyTorch Lamb optimizer w/ behaviour similar to NVIDIA FusedLamb
This optimizer code was adapted from the following (starting with latest)
* https://github.com/HabanaAI/Model-References/blob/2b435114fe8e31f159b1d3063b8280ae37af7423/PyTorch/nlp/bert/pretraining/lamb.py
* https://github.com/NVIDIA/DeepLearningExample... | pytorch-image-models/timm/optim/lamb.py/0 | {
"file_path": "pytorch-image-models/timm/optim/lamb.py",
"repo_id": "pytorch-image-models",
"token_count": 3768
} | 174 |
""" Plateau Scheduler
Adapts PyTorch plateau scheduler and allows application of noise, warmup.
Hacked together by / Copyright 2020 Ross Wightman
"""
import torch
from .scheduler import Scheduler
class PlateauLRScheduler(Scheduler):
"""Decay the LR by a factor every time the validation loss plateaus."""
d... | pytorch-image-models/timm/scheduler/plateau_lr.py/0 | {
"file_path": "pytorch-image-models/timm/scheduler/plateau_lr.py",
"repo_id": "pytorch-image-models",
"token_count": 1800
} | 175 |
""" Misc utils
Hacked together by / Copyright 2020 Ross Wightman
"""
import argparse
import ast
import re
def natural_key(string_):
"""See http://www.codinghorror.com/blog/archives/001018.html"""
return [int(s) if s.isdigit() else s for s in re.split(r'(\d+)', string_.lower())]
def add_bool_arg(parser, nam... | pytorch-image-models/timm/utils/misc.py/0 | {
"file_path": "pytorch-image-models/timm/utils/misc.py",
"repo_id": "pytorch-image-models",
"token_count": 451
} | 176 |
mod app;
mod event;
mod generation;
mod table;
mod utils;
use crate::app::App;
use crate::event::Event;
use crossterm::ExecutableCommand;
use std::io;
use text_generation_client::{NextTokenChooserParameters, ShardedClient};
use tokenizers::Tokenizer;
use tokio::sync::{broadcast, mpsc};
use tui::backend::CrosstermBacke... | text-generation-inference/benchmark/src/lib.rs/0 | {
"file_path": "text-generation-inference/benchmark/src/lib.rs",
"repo_id": "text-generation-inference",
"token_count": 1852
} | 177 |
from typing import Dict
# Text Generation Inference Errors
class ValidationError(Exception):
def __init__(self, message: str):
super().__init__(message)
class GenerationError(Exception):
def __init__(self, message: str):
super().__init__(message)
class OverloadedError(Exception):
def _... | text-generation-inference/clients/python/text_generation/errors.py/0 | {
"file_path": "text-generation-inference/clients/python/text_generation/errors.py",
"repo_id": "text-generation-inference",
"token_count": 1080
} | 178 |
# Streaming
## What is Streaming?
Token streaming is the mode in which the server returns the tokens one by one as the model generates them. This enables showing progressive generations to the user rather than waiting for the whole generation. Streaming is an essential aspect of the end-user experience as it reduces ... | text-generation-inference/docs/source/conceptual/streaming.md/0 | {
"file_path": "text-generation-inference/docs/source/conceptual/streaming.md",
"repo_id": "text-generation-inference",
"token_count": 1981
} | 179 |
[
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [
{
"id": 1,
"logprob": null,
"text": "<s>"
},
{
"id": 1724,
"logprob": -7.6914062,
"text": "What"
... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_awq_sharded/test_flash_llama_awq_load_sharded.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_awq_sharded/test_flash_llama_awq_load_sharded.json",
"repo_id": "text-generation-inference",
"token_count": 5776
} | 180 |
[
{
"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"
... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_mistral/test_flash_mistral_load.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_mistral/test_flash_mistral_load.json",
"repo_id": "text-generation-inference",
"token_count": 4897
} | 181 |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [
{
"id": 1,
"logprob": null,
"text": "<s>"
},
{
"id": 4911,
"logprob": -6.9765625,
"text": "User"
},
{
"id": 29... | text-generation-inference/integration-tests/models/__snapshots__/test_idefics/test_idefics.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_idefics/test_idefics.json",
"repo_id": "text-generation-inference",
"token_count": 2062
} | 182 |
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": 624
} | 183 |
import pytest
@pytest.fixture(scope="module")
def neox_sharded_handle(launcher):
with launcher(
"OpenAssistant/oasst-sft-1-pythia-12b", num_shard=2, use_flash_attention=False
) as handle:
yield handle
@pytest.fixture(scope="module")
async def neox_sharded(neox_sharded_handle):
await neox... | text-generation-inference/integration-tests/models/test_neox_sharded.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_neox_sharded.py",
"repo_id": "text-generation-inference",
"token_count": 507
} | 184 |
# Router
Also named `webserver` throughout the docs.
This router is handling most of the logic to handle the "batches" tell
when to pass new `prefill` requests and pausing `decode` requests, which ones etc...
It uses gRPC to communicate with the shards which can therefore be kept
much simpler and focus on having the... | text-generation-inference/router/README.md/0 | {
"file_path": "text-generation-inference/router/README.md",
"repo_id": "text-generation-inference",
"token_count": 1177
} | 185 |
/// Payload validation logic
use crate::validation::ValidationError::{BestOfSampling, BestOfSeed, EmptyInput};
use crate::{GenerateParameters, GenerateRequest};
use rand::{thread_rng, Rng};
use text_generation_client::{NextTokenChooserParameters, StoppingCriteriaParameters};
use thiserror::Error;
use tokenizers::tokeni... | text-generation-inference/router/src/validation.rs/0 | {
"file_path": "text-generation-inference/router/src/validation.rs",
"repo_id": "text-generation-inference",
"token_count": 11273
} | 186 |
// Adapted from turboderp exllama: https://github.com/turboderp/exllama
#ifndef _cuda_buffers_cuh
#define _cuda_buffers_cuh
#include <cuda_runtime.h>
#include <cuda_fp16.h>
#include <cstdint>
#include <cstdio>
const int CUDA_MAX_DEVICES = 16;
// #ifndef _cuda_buffers_cu
// extern __constant__ half2 q4_table[16][256... | text-generation-inference/server/exllama_kernels/exllama_kernels/cuda_buffers.cuh/0 | {
"file_path": "text-generation-inference/server/exllama_kernels/exllama_kernels/cuda_buffers.cuh",
"repo_id": "text-generation-inference",
"token_count": 471
} | 187 |
#ifndef _matrix_view_cuh
#define _matrix_view_cuh
#include <cuda_runtime.h>
#include <cuda_fp16.h>
#include "quant/qdq_util.cuh"
class MatrixView_half
{
public:
const half* data;
const int height;
const int width;
__device__ __forceinline__ MatrixView_half(const half* data, const int height, const i... | text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/matrix_view.cuh/0 | {
"file_path": "text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/matrix_view.cuh",
"repo_id": "text-generation-inference",
"token_count": 1861
} | 188 |
from setuptools import setup
from torch.utils.cpp_extension import BuildExtension, CUDAExtension
import torch
extra_cuda_cflags = ["-lineinfo", "-O3"]
if torch.version.hip:
extra_cuda_cflags += ["-DHIPBLAS_USE_HIP_HALF"]
extra_compile_args = {
"nvcc": extra_cuda_cflags,
}
setup(
name="exllamav2_kernels"... | text-generation-inference/server/exllamav2_kernels/setup.py/0 | {
"file_path": "text-generation-inference/server/exllamav2_kernels/setup.py",
"repo_id": "text-generation-inference",
"token_count": 363
} | 189 |
# 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 | {
"file_path": "text-generation-inference/server/tests/utils/test_watermark.py",
"repo_id": "text-generation-inference",
"token_count": 781
} | 190 |
import torch
import torch.distributed
from torch import nn
from transformers.modeling_utils import PreTrainedModel
from transformers.configuration_utils import PretrainedConfig
from typing import Optional, List, Tuple
from text_generation_server.utils import paged_attention, flash_attn
from text_generation_server.uti... | text-generation-inference/server/text_generation_server/models/custom_modeling/flash_rw_modeling.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/models/custom_modeling/flash_rw_modeling.py",
"repo_id": "text-generation-inference",
"token_count": 10032
} | 191 |
import torch
from typing import Optional
from text_generation_server.models.flash_mistral import BaseFlashMistral
from text_generation_server.models.custom_modeling.flash_mixtral_modeling import (
MixtralConfig,
FlashMixtralForCausalLM,
)
class FlashMixtral(BaseFlashMistral):
def __init__(
self,... | text-generation-inference/server/text_generation_server/models/flash_mixtral.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/models/flash_mixtral.py",
"repo_id": "text-generation-inference",
"token_count": 379
} | 192 |
import torch
import torch.distributed
from typing import List, Optional, Tuple
from transformers import (
AutoTokenizer,
AutoConfig,
)
from text_generation_server.models import Seq2SeqLM
from text_generation_server.models.custom_modeling.t5_modeling import (
T5ForConditionalGeneration,
)
from text_genera... | text-generation-inference/server/text_generation_server/models/t5.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/models/t5.py",
"repo_id": "text-generation-inference",
"token_count": 1617
} | 193 |
import torch
IS_ROCM_SYSTEM = torch.version.hip is not None
IS_CUDA_SYSTEM = torch.version.cuda is not None
| text-generation-inference/server/text_generation_server/utils/import_utils.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/utils/import_utils.py",
"repo_id": "text-generation-inference",
"token_count": 40
} | 194 |
# `tokenizers-darwin-x64`
This is the **x86_64-apple-darwin** binary for `tokenizers`
| tokenizers/bindings/node/npm/darwin-x64/README.md/0 | {
"file_path": "tokenizers/bindings/node/npm/darwin-x64/README.md",
"repo_id": "tokenizers",
"token_count": 34
} | 195 |
# `tokenizers-win32-ia32-msvc`
This is the **i686-pc-windows-msvc** binary for `tokenizers`
| tokenizers/bindings/node/npm/win32-ia32-msvc/README.md/0 | {
"file_path": "tokenizers/bindings/node/npm/win32-ia32-msvc/README.md",
"repo_id": "tokenizers",
"token_count": 37
} | 196 |
extern crate tokenizers as tk;
use crate::encoding::*;
use crate::tokenizer::Tokenizer;
use napi::bindgen_prelude::*;
use tk::tokenizer::{EncodeInput, Encoding};
pub struct EncodeTask<'s> {
pub tokenizer: Tokenizer,
pub input: Option<EncodeInput<'s>>,
pub add_special_tokens: bool,
}
impl Task for EncodeTask<'s... | tokenizers/bindings/node/src/tasks/tokenizer.rs/0 | {
"file_path": "tokenizers/bindings/node/src/tasks/tokenizer.rs",
"repo_id": "tokenizers",
"token_count": 1295
} | 197 |
import argparse
import logging
import time
from tqdm import tqdm
logging.getLogger("transformers").disabled = True
logging.getLogger("transformers.tokenization_utils").disabled = True
from tokenizers import Tokenizer, decoders, pre_tokenizers
from tokenizers.models import BPE, WordPiece
from tokenizers.normalizers ... | tokenizers/bindings/python/examples/example.py/0 | {
"file_path": "tokenizers/bindings/python/examples/example.py",
"repo_id": "tokenizers",
"token_count": 1783
} | 198 |
# Generated content DO NOT EDIT
from .. import models
Model = models.Model
BPE = models.BPE
Unigram = models.Unigram
WordLevel = models.WordLevel
WordPiece = models.WordPiece
| tokenizers/bindings/python/py_src/tokenizers/models/__init__.py/0 | {
"file_path": "tokenizers/bindings/python/py_src/tokenizers/models/__init__.py",
"repo_id": "tokenizers",
"token_count": 56
} | 199 |
from argparse import ArgumentParser
from json import dump
from logging import basicConfig, getLogger
from os import linesep, remove
from os.path import exists
from tempfile import NamedTemporaryFile
from typing import Dict, List, Tuple
from requests import get
from sentencepiece import SentencePieceProcessor
from tqdm... | tokenizers/bindings/python/scripts/sentencepiece_extractor.py/0 | {
"file_path": "tokenizers/bindings/python/scripts/sentencepiece_extractor.py",
"repo_id": "tokenizers",
"token_count": 2267
} | 200 |
use super::regex::PyRegex;
use super::{DestroyPtr, RefMutContainer, RefMutGuard};
use crate::error::ToPyResult;
use pyo3::exceptions;
use pyo3::prelude::*;
use pyo3::types::*;
use tk::normalizer::{char_to_bytes, NormalizedString, Range, SplitDelimiterBehavior};
use tk::pattern::Pattern;
/// Represents a Pattern as use... | tokenizers/bindings/python/src/utils/normalization.rs/0 | {
"file_path": "tokenizers/bindings/python/src/utils/normalization.rs",
"repo_id": "tokenizers",
"token_count": 8467
} | 201 |
from tokenizers import Tokenizer
from ..utils import data_dir, doc_pipeline_bert_tokenizer, doc_wiki_tokenizer
disable_printing = True
original_print = print
def print(*args, **kwargs):
if not disable_printing:
original_print(*args, **kwargs)
class TestPipeline:
def test_pipeline(self, doc_wiki_t... | tokenizers/bindings/python/tests/documentation/test_pipeline.py/0 | {
"file_path": "tokenizers/bindings/python/tests/documentation/test_pipeline.py",
"repo_id": "tokenizers",
"token_count": 3351
} | 202 |
# Encode Inputs
<tokenizerslangcontent>
<python>
These types represent all the different kinds of input that a [`~tokenizers.Tokenizer`] accepts
when using [`~tokenizers.Tokenizer.encode_batch`].
## TextEncodeInput[[[[tokenizers.TextEncodeInput]]]]
<code>tokenizers.TextEncodeInput</code>
Represents a textual input ... | tokenizers/docs/source-doc-builder/api/encode-inputs.mdx/0 | {
"file_path": "tokenizers/docs/source-doc-builder/api/encode-inputs.mdx",
"repo_id": "tokenizers",
"token_count": 716
} | 203 |
from collections import defaultdict, abc
from typing import cast
from docutils import nodes
from docutils.parsers.rst import Directive
import sphinx
from sphinx.locale import _
from sphinx.util.docutils import SphinxDirective
from sphinx.errors import ExtensionError
from conf import languages as LANGUAGES
logger = ... | tokenizers/docs/source/_ext/entities.py/0 | {
"file_path": "tokenizers/docs/source/_ext/entities.py",
"repo_id": "tokenizers",
"token_count": 4032
} | 204 |
.. entities:: python
:global:
class
class
classmethod
class method
Tokenizer
:class:`~tokenizers.Tokenizer`
Tokenizer.train
:meth:`~tokenizers.Tokenizer.train`
Tokenizer.save
:meth:`~tokenizers.Tokenizer.save`
Tokenizer.from_file
:meth:`~toke... | tokenizers/docs/source/entities.inc/0 | {
"file_path": "tokenizers/docs/source/entities.inc",
"repo_id": "tokenizers",
"token_count": 2078
} | 205 |
#[macro_use]
extern crate criterion;
mod common;
use std::fs::File;
use std::io::{BufRead, BufReader};
use std::path::Path;
use criterion::Criterion;
use tokenizers::models::bpe::{BpeTrainerBuilder, BPE};
use tokenizers::models::TrainerWrapper;
use tokenizers::pre_tokenizers::byte_level::ByteLevel;
use tokenizers::p... | tokenizers/tokenizers/benches/bpe_benchmark.rs/0 | {
"file_path": "tokenizers/tokenizers/benches/bpe_benchmark.rs",
"repo_id": "tokenizers",
"token_count": 1621
} | 206 |
<div align="center">
<h1><code>create-wasm-app</code></h1>
<strong>An <code>npm init</code> template for kick starting a project that uses NPM packages containing Rust-generated WebAssembly and bundles them with Webpack.</strong>
<p>
<a href="https://travis-ci.org/rustwasm/create-wasm-app"><img src="https:... | tokenizers/tokenizers/examples/unstable_wasm/www/README.md/0 | {
"file_path": "tokenizers/tokenizers/examples/unstable_wasm/www/README.md",
"repo_id": "tokenizers",
"token_count": 893
} | 207 |
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
} | 208 |
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 | {
"file_path": "tokenizers/tokenizers/src/models/wordlevel/trainer.rs",
"repo_id": "tokenizers",
"token_count": 2735
} | 209 |
use crate::tokenizer::{Decoder, PreTokenizedString, PreTokenizer, Result, SplitDelimiterBehavior};
use serde::{Deserialize, Deserializer, Serialize};
/// Enum representing options for the metaspace prepending scheme.
#[derive(Debug, Clone, PartialEq, Serialize, Eq, Deserialize, Copy)]
#[serde(rename_all = "snake_case"... | tokenizers/tokenizers/src/pre_tokenizers/metaspace.rs/0 | {
"file_path": "tokenizers/tokenizers/src/pre_tokenizers/metaspace.rs",
"repo_id": "tokenizers",
"token_count": 6508
} | 210 |
//! Represents a tokenization pipeline.
//!
//! A [`Tokenizer`](struct.Tokenizer.html) is composed of some of the following parts.
//! - [`Normalizer`](trait.Normalizer.html): Takes care of the text normalization (like unicode normalization).
//! - [`PreTokenizer`](trait.PreTokenizer.html): Takes care of the pre to... | tokenizers/tokenizers/src/tokenizer/mod.rs/0 | {
"file_path": "tokenizers/tokenizers/src/tokenizer/mod.rs",
"repo_id": "tokenizers",
"token_count": 18666
} | 211 |
use tokenizers::decoders::wordpiece::WordPiece as WordPieceDecoder;
use tokenizers::models::bpe::BPE;
use tokenizers::models::wordpiece::WordPiece;
use tokenizers::normalizers::bert::BertNormalizer;
use tokenizers::pre_tokenizers::bert::BertPreTokenizer;
use tokenizers::pre_tokenizers::byte_level::ByteLevel;
use tokeni... | tokenizers/tokenizers/tests/common/mod.rs/0 | {
"file_path": "tokenizers/tokenizers/tests/common/mod.rs",
"repo_id": "tokenizers",
"token_count": 771
} | 212 |
.PHONY: deps_table_update modified_only_fixup extra_style_checks quality style fixup fix-copies test test-examples
# make sure to test the local checkout in scripts and not the pre-installed one (don't use quotes!)
export PYTHONPATH = src
check_dirs := examples tests src utils
exclude_folders := examples/research_pr... | transformers/Makefile/0 | {
"file_path": "transformers/Makefile",
"repo_id": "transformers",
"token_count": 1325
} | 213 |
FROM python:3.10
LABEL maintainer="Hugging Face"
RUN apt update
RUN git clone https://github.com/huggingface/transformers
RUN python3 -m pip install --no-cache-dir --upgrade pip && python3 -m pip install --no-cache-dir git+https://github.com/huggingface/doc-builder ./transformers[dev]
RUN apt-get -y update && apt-get... | transformers/docker/transformers-doc-builder/Dockerfile/0 | {
"file_path": "transformers/docker/transformers-doc-builder/Dockerfile",
"repo_id": "transformers",
"token_count": 292
} | 214 |
<!--Copyright 2022 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | transformers/docs/source/de/run_scripts.md/0 | {
"file_path": "transformers/docs/source/de/run_scripts.md",
"repo_id": "transformers",
"token_count": 7455
} | 215 |
<!--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/chat_templating.md/0 | {
"file_path": "transformers/docs/source/en/chat_templating.md",
"repo_id": "transformers",
"token_count": 6714
} | 216 |
<!--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/clipseg.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/clipseg.md",
"repo_id": "transformers",
"token_count": 1221
} | 217 |
<!--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/deformable_detr.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/deformable_detr.md",
"repo_id": "transformers",
"token_count": 1014
} | 218 |
<!--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/electra.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/electra.md",
"repo_id": "transformers",
"token_count": 2211
} | 219 |
<!--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/fuyu.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/fuyu.md",
"repo_id": "transformers",
"token_count": 1655
} | 220 |
<!--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/idefics.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/idefics.md",
"repo_id": "transformers",
"token_count": 776
} | 221 |
<!--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/longformer.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/longformer.md",
"repo_id": "transformers",
"token_count": 2395
} | 222 |
<!--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/nat.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/nat.md",
"repo_id": "transformers",
"token_count": 1229
} | 223 |
<!--Copyright 2021 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | transformers/docs/source/en/model_doc/perceiver.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/perceiver.md",
"repo_id": "transformers",
"token_count": 2762
} | 224 |
<!--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/rembert.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/rembert.md",
"repo_id": "transformers",
"token_count": 1363
} | 225 |
<!--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/speech_to_text.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/speech_to_text.md",
"repo_id": "transformers",
"token_count": 1920
} | 226 |
<!--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/vision-encoder-decoder.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/vision-encoder-decoder.md",
"repo_id": "transformers",
"token_count": 2525
} | 227 |
<!--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/whisper.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/whisper.md",
"repo_id": "transformers",
"token_count": 1994
} | 228 |
<!--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/perplexity.md/0 | {
"file_path": "transformers/docs/source/en/perplexity.md",
"repo_id": "transformers",
"token_count": 2258
} | 229 |
<!--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/image_captioning.md/0 | {
"file_path": "transformers/docs/source/en/tasks/image_captioning.md",
"repo_id": "transformers",
"token_count": 2702
} | 230 |
<!--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/tasks/translation.md/0 | {
"file_path": "transformers/docs/source/en/tasks/translation.md",
"repo_id": "transformers",
"token_count": 5199
} | 231 |
- sections:
- local: index
title: 🤗 Transformers
- local: quicktour
title: Tour rápido
- local: installation
title: Instalación
title: Empezar
- sections:
- local: pipeline_tutorial
title: Pipelines para inferencia
- local: autoclass_tutorial
title: Carga instancias preentrenadas con un... | transformers/docs/source/es/_toctree.yml/0 | {
"file_path": "transformers/docs/source/es/_toctree.yml",
"repo_id": "transformers",
"token_count": 948
} | 232 |
<!--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/autoclass_tutorial.md/0 | {
"file_path": "transformers/docs/source/it/autoclass_tutorial.md",
"repo_id": "transformers",
"token_count": 1933
} | 233 |
<!--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/model_doc/audio-spectrogram-transformer.md/0 | {
"file_path": "transformers/docs/source/ja/model_doc/audio-spectrogram-transformer.md",
"repo_id": "transformers",
"token_count": 2249
} | 234 |
<!--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/ja/model_doc/blenderbot-small.md/0 | {
"file_path": "transformers/docs/source/ja/model_doc/blenderbot-small.md",
"repo_id": "transformers",
"token_count": 1831
} | 235 |
<!--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/code_llama.md/0 | {
"file_path": "transformers/docs/source/ja/model_doc/code_llama.md",
"repo_id": "transformers",
"token_count": 4010
} | 236 |
<!--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/deplot.md/0 | {
"file_path": "transformers/docs/source/ja/model_doc/deplot.md",
"repo_id": "transformers",
"token_count": 2027
} | 237 |
<!--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/run_scripts.md/0 | {
"file_path": "transformers/docs/source/ja/run_scripts.md",
"repo_id": "transformers",
"token_count": 8185
} | 238 |
<!--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/prompting.md/0 | {
"file_path": "transformers/docs/source/ja/tasks/prompting.md",
"repo_id": "transformers",
"token_count": 9967
} | 239 |
<!--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/tokenizer_summary.md/0 | {
"file_path": "transformers/docs/source/ja/tokenizer_summary.md",
"repo_id": "transformers",
"token_count": 9811
} | 240 |
<!---
Copyright 2020 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or ... | transformers/docs/source/ko/contributing.md/0 | {
"file_path": "transformers/docs/source/ko/contributing.md",
"repo_id": "transformers",
"token_count": 15871
} | 241 |
<!--⚠️ 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.
-->
# 웹 서버를 위한 파이프라인 사용하기[[using_pipelines_for_a_webserver]]
<Tip>
추론 엔진을 만드는 것은 복잡한 주제이며, "최선의" 솔루션은 문제 공간에 따라 달라질 가능성이 높습니다. CPU 또는 GPU를 사용하는지에 따라 다르고... | transformers/docs/source/ko/pipeline_webserver.md/0 | {
"file_path": "transformers/docs/source/ko/pipeline_webserver.md",
"repo_id": "transformers",
"token_count": 6174
} | 242 |
<!--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/tokenizer_summary.md/0 | {
"file_path": "transformers/docs/source/ko/tokenizer_summary.md",
"repo_id": "transformers",
"token_count": 15141
} | 243 |
<!--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/multilingual.md/0 | {
"file_path": "transformers/docs/source/pt/multilingual.md",
"repo_id": "transformers",
"token_count": 3154
} | 244 |
<!--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/zh/big_models.md/0 | {
"file_path": "transformers/docs/source/zh/big_models.md",
"repo_id": "transformers",
"token_count": 3096
} | 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/zh/serialization.md/0 | {
"file_path": "transformers/docs/source/zh/serialization.md",
"repo_id": "transformers",
"token_count": 4917
} | 246 |
#!/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_bart_dlm_flax.py/0 | {
"file_path": "transformers/examples/flax/language-modeling/run_bart_dlm_flax.py",
"repo_id": "transformers",
"token_count": 18354
} | 247 |
<!---
Copyright 2021 The Google Flax Team Authors and 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 r... | transformers/examples/flax/text-classification/README.md/0 | {
"file_path": "transformers/examples/flax/text-classification/README.md",
"repo_id": "transformers",
"token_count": 2757
} | 248 |
<!---
Copyright 2020 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or ... | transformers/examples/legacy/seq2seq/README.md/0 | {
"file_path": "transformers/examples/legacy/seq2seq/README.md",
"repo_id": "transformers",
"token_count": 5081
} | 249 |
### Motivation
Without processing, english-> romanian mbart-large-en-ro gets BLEU score 26.8 on the WMT data.
With post processing, it can score 37..
Here is the postprocessing code, stolen from @mjpost in this [issue](https://github.com/pytorch/fairseq/issues/1758)
### Instructions
Note: You need to have your test_... | transformers/examples/legacy/seq2seq/romanian_postprocessing.md/0 | {
"file_path": "transformers/examples/legacy/seq2seq/romanian_postprocessing.md",
"repo_id": "transformers",
"token_count": 723
} | 250 |
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
logger = logging.getLogger(__name__)
class NER(TokenClassificationTask):
def __init__(self, label_idx=-1):
# in NER datasets, the last column ... | transformers/examples/legacy/token-classification/tasks.py/0 | {
"file_path": "transformers/examples/legacy/token-classification/tasks.py",
"repo_id": "transformers",
"token_count": 3163
} | 251 |
# 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... | transformers/examples/pytorch/old_test_xla_examples.py/0 | {
"file_path": "transformers/examples/pytorch/old_test_xla_examples.py",
"repo_id": "transformers",
"token_count": 1245
} | 252 |
#!/usr/bin/env python
# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LI... | transformers/examples/pytorch/text-classification/run_glue.py/0 | {
"file_path": "transformers/examples/pytorch/text-classification/run_glue.py",
"repo_id": "transformers",
"token_count": 11733
} | 253 |
# coding=utf-8
# Copyright 2019 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 copy of the License at
#
# http://www.a... | transformers/examples/research_projects/bertabs/configuration_bertabs.py/0 | {
"file_path": "transformers/examples/research_projects/bertabs/configuration_bertabs.py",
"repo_id": "transformers",
"token_count": 1345
} | 254 |
from arguments import TokenizerTrainingArguments
from datasets import load_dataset
from tqdm import tqdm
from transformers import AutoTokenizer, HfArgumentParser
from transformers.models.gpt2.tokenization_gpt2 import bytes_to_unicode
# Iterator for Training
def batch_iterator(batch_size=10):
for _ in tqdm(range(... | transformers/examples/research_projects/codeparrot/scripts/bpe_training.py/0 | {
"file_path": "transformers/examples/research_projects/codeparrot/scripts/bpe_training.py",
"repo_id": "transformers",
"token_count": 347
} | 255 |
from __future__ import absolute_import, division, print_function
import argparse
import glob
import logging
import os
import random
import time
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, TensorDataset
from torch.utils.data.distribute... | transformers/examples/research_projects/deebert/run_glue_deebert.py/0 | {
"file_path": "transformers/examples/research_projects/deebert/run_glue_deebert.py",
"repo_id": "transformers",
"token_count": 13897
} | 256 |
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