text stringlengths 7 328k | id stringlengths 14 166 | metadata dict | __index_level_0__ int64 0 459 |
|---|---|---|---|
""" Linear layer (alternate definition)
"""
import torch
import torch.nn.functional as F
from torch import nn as nn
class Linear(nn.Linear):
r"""Applies a linear transformation to the incoming data: :math:`y = xA^T + b`
Wraps torch.nn.Linear to support AMP + torchscript usage by manually casting
weight &... | pytorch-image-models/timm/layers/linear.py/0 | {
"file_path": "pytorch-image-models/timm/layers/linear.py",
"repo_id": "pytorch-image-models",
"token_count": 282
} | 186 |
""" Depthwise Separable Conv Modules
Basic DWS convs. Other variations of DWS exist with batch norm or activations between the
DW and PW convs such as the Depthwise modules in MobileNetV2 / EfficientNet and Xception.
Hacked together by / Copyright 2020 Ross Wightman
"""
from torch import nn as nn
from .create_conv2d... | pytorch-image-models/timm/layers/separable_conv.py/0 | {
"file_path": "pytorch-image-models/timm/layers/separable_conv.py",
"repo_id": "pytorch-image-models",
"token_count": 1138
} | 187 |
import dataclasses
import logging
import os
from copy import deepcopy
from typing import Optional, Dict, Callable, Any, Tuple
from torch import nn as nn
from torch.hub import load_state_dict_from_url
from timm.models._features import FeatureListNet, FeatureHookNet
from timm.models._features_fx import FeatureGraphNet
... | pytorch-image-models/timm/models/_builder.py/0 | {
"file_path": "pytorch-image-models/timm/models/_builder.py",
"repo_id": "pytorch-image-models",
"token_count": 7677
} | 188 |
""" Model Registry
Hacked together by / Copyright 2020 Ross Wightman
"""
import fnmatch
import re
import sys
import warnings
from collections import defaultdict, deque
from copy import deepcopy
from dataclasses import replace
from typing import Any, Callable, Dict, Iterable, List, Optional, Set, Sequence, Union, Tuple... | pytorch-image-models/timm/models/_registry.py/0 | {
"file_path": "pytorch-image-models/timm/models/_registry.py",
"repo_id": "pytorch-image-models",
"token_count": 5428
} | 189 |
""" EdgeNeXt
Paper: `EdgeNeXt: Efficiently Amalgamated CNN-Transformer Architecture for Mobile Vision Applications`
- https://arxiv.org/abs/2206.10589
Original code and weights from https://github.com/mmaaz60/EdgeNeXt
Modifications and additions for timm by / Copyright 2022, Ross Wightman
"""
import math
from colle... | pytorch-image-models/timm/models/edgenext.py/0 | {
"file_path": "pytorch-image-models/timm/models/edgenext.py",
"repo_id": "pytorch-image-models",
"token_count": 11040
} | 190 |
""" PP-HGNet (V1 & V2)
Reference:
https://github.com/PaddlePaddle/PaddleClas/blob/develop/docs/zh_CN/models/ImageNet1k/PP-HGNetV2.md
The Paddle Implement of PP-HGNet (https://github.com/PaddlePaddle/PaddleClas/blob/release/2.5.1/docs/en/models/PP-HGNet_en.md)
PP-HGNet: https://github.com/PaddlePaddle/PaddleClas/blob/r... | pytorch-image-models/timm/models/hgnet.py/0 | {
"file_path": "pytorch-image-models/timm/models/hgnet.py",
"repo_id": "pytorch-image-models",
"token_count": 13284
} | 191 |
""" Nested Transformer (NesT) in PyTorch
A PyTorch implement of Aggregating Nested Transformers as described in:
'Aggregating Nested Transformers'
- https://arxiv.org/abs/2105.12723
The official Jax code is released and available at https://github.com/google-research/nested-transformer. The weights
have been con... | pytorch-image-models/timm/models/nest.py/0 | {
"file_path": "pytorch-image-models/timm/models/nest.py",
"repo_id": "pytorch-image-models",
"token_count": 10075
} | 192 |
"""
SEResNet implementation from Cadene's pretrained models
https://github.com/Cadene/pretrained-models.pytorch/blob/master/pretrainedmodels/models/senet.py
Additional credit to https://github.com/creafz
Original model: https://github.com/hujie-frank/SENet
ResNet code gently borrowed from
https://github.com/pytorch/v... | pytorch-image-models/timm/models/senet.py/0 | {
"file_path": "pytorch-image-models/timm/models/senet.py",
"repo_id": "pytorch-image-models",
"token_count": 8344
} | 193 |
""" Vision OutLOoker (VOLO) implementation
Paper: `VOLO: Vision Outlooker for Visual Recognition` - https://arxiv.org/abs/2106.13112
Code adapted from official impl at https://github.com/sail-sg/volo, original copyright in comment below
Modifications and additions for timm by / Copyright 2022, Ross Wightman
"""
# Co... | pytorch-image-models/timm/models/volo.py/0 | {
"file_path": "pytorch-image-models/timm/models/volo.py",
"repo_id": "pytorch-image-models",
"token_count": 15802
} | 194 |
""" PyTorch MADGRAD optimizer
MADGRAD: https://arxiv.org/abs/2101.11075
Code from: https://github.com/facebookresearch/madgrad
"""
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import ma... | pytorch-image-models/timm/optim/madgrad.py/0 | {
"file_path": "pytorch-image-models/timm/optim/madgrad.py",
"repo_id": "pytorch-image-models",
"token_count": 3505
} | 195 |
""" Step Scheduler
Basic step LR schedule with warmup, noise.
Hacked together by / Copyright 2020 Ross Wightman
"""
import math
import torch
from .scheduler import Scheduler
class StepLRScheduler(Scheduler):
"""
"""
def __init__(
self,
optimizer: torch.optim.Optimizer,
... | pytorch-image-models/timm/scheduler/step_lr.py/0 | {
"file_path": "pytorch-image-models/timm/scheduler/step_lr.py",
"repo_id": "pytorch-image-models",
"token_count": 939
} | 196 |
import random
import numpy as np
import torch
def random_seed(seed=42, rank=0):
torch.manual_seed(seed + rank)
np.random.seed(seed + rank)
random.seed(seed + rank)
| pytorch-image-models/timm/utils/random.py/0 | {
"file_path": "pytorch-image-models/timm/utils/random.py",
"repo_id": "pytorch-image-models",
"token_count": 68
} | 197 |
use crate::app::Data;
use tabled::settings::Merge;
use tabled::{builder::Builder, settings::Style, Table};
#[allow(clippy::too_many_arguments)]
pub(crate) fn parameters_table(
tokenizer_name: String,
sequence_length: u32,
decode_length: u32,
top_n_tokens: Option<u32>,
n_runs: usize,
warmups: us... | text-generation-inference/benchmark/src/table.rs/0 | {
"file_path": "text-generation-inference/benchmark/src/table.rs",
"repo_id": "text-generation-inference",
"token_count": 2298
} | 198 |
from enum import Enum
from pydantic import BaseModel, validator
from typing import Optional, List, Union, Any
from text_generation.errors import ValidationError
# enum for grammar type
class GrammarType(str, Enum):
Json = "json"
Regex = "regex"
# Grammar type and value
class Grammar(BaseModel):
# Gramm... | text-generation-inference/clients/python/text_generation/types.py/0 | {
"file_path": "text-generation-inference/clients/python/text_generation/types.py",
"repo_id": "text-generation-inference",
"token_count": 4249
} | 199 |
# 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": 1972
} | 200 |
[
{
"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
} | 201 |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [
{
"id": 1,
"logprob": null,
"text": "<s>"
},
{
"id": 4321,
"logprob": -9.7890625,
"text": "Test"
},
{
"id": 20... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_llama_gptq/test_flash_llama_gptq.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_llama_gptq/test_flash_llama_gptq.json",
"repo_id": "text-generation-inference",
"token_count": 1046
} | 202 |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [
{
"id": 2271,
"logprob": null,
"text": "Test"
},
{
"id": 1681,
"logprob": -8.8515625,
"text": " request"
}
],
"seed"... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_qwen2/test_flash_qwen2.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_qwen2/test_flash_qwen2.json",
"repo_id": "text-generation-inference",
"token_count": 988
} | 203 |
[
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [
{
"id": 1,
"logprob": null,
"text": "<s>"
},
{
"id": 4911,
"logprob": -6.9804688,
"text": "User"
... | text-generation-inference/integration-tests/models/__snapshots__/test_idefics/test_idefics_load.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_idefics/test_idefics_load.json",
"repo_id": "text-generation-inference",
"token_count": 9573
} | 204 |
{
"choices": [
{
"finish_reason": "eos_token",
"index": 0,
"logprobs": null,
"message": {
"content": null,
"name": null,
"role": "assistant",
"tool_calls": {
"function": {
"description": null,
"name": "tools",
"p... | text-generation-inference/integration-tests/models/__snapshots__/test_tools_llama/test_flash_llama_grammar_tools.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_tools_llama/test_flash_llama_grammar_tools.json",
"repo_id": "text-generation-inference",
"token_count": 469
} | 205 |
import pytest
@pytest.fixture(scope="module")
def flash_neox_sharded_handle(launcher):
with launcher("OpenAssistant/oasst-sft-1-pythia-12b", num_shard=2) as handle:
yield handle
@pytest.fixture(scope="module")
async def flash_neox_sharded(flash_neox_sharded_handle):
await flash_neox_sharded_handle.h... | text-generation-inference/integration-tests/models/test_flash_neox_sharded.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_flash_neox_sharded.py",
"repo_id": "text-generation-inference",
"token_count": 491
} | 206 |
[package]
name = "text-generation-client"
version.workspace = true
edition.workspace = true
authors.workspace = true
homepage.workspace = true
[dependencies]
futures = "^0.3"
grpc-metadata = { path = "../grpc-metadata" }
prost = "^0.12"
thiserror = "^1.0"
tokio = { version = "^1.32", features = ["sync"] }
tonic = "^0.... | text-generation-inference/router/client/Cargo.toml/0 | {
"file_path": "text-generation-inference/router/client/Cargo.toml",
"repo_id": "text-generation-inference",
"token_count": 180
} | 207 |
#!/bin/bash
if [[ -z "${HF_MODEL_ID}" ]]; then
echo "HF_MODEL_ID must be set"
exit 1
fi
export MODEL_ID="${HF_MODEL_ID}"
if [[ -n "${HF_MODEL_REVISION}" ]]; then
export REVISION="${HF_MODEL_REVISION}"
fi
if [[ -n "${SM_NUM_GPUS}" ]]; then
export NUM_SHARD="${SM_NUM_GPUS}"
fi
if [[ -n "${HF_MODEL_QUANTIZE}" ... | text-generation-inference/sagemaker-entrypoint.sh/0 | {
"file_path": "text-generation-inference/sagemaker-entrypoint.sh",
"repo_id": "text-generation-inference",
"token_count": 239
} | 208 |
// Adapted from turboderp exllama: https://github.com/turboderp/exllama
#include "column_remap.cuh"
#include "../util.cuh"
const int SHUF_BLOCKSIZE_X = 256;
const int SHUF_BLOCKSIZE_Y = 16;
__global__ void column_remap_kernel
(
const half* __restrict__ x,
half* __restrict__ x_new,
const int x_width,
... | text-generation-inference/server/exllama_kernels/exllama_kernels/cuda_func/column_remap.cu/0 | {
"file_path": "text-generation-inference/server/exllama_kernels/exllama_kernels/cuda_func/column_remap.cu",
"repo_id": "text-generation-inference",
"token_count": 696
} | 209 |
#include "q_gemm.cuh"
#include "util.cuh"
#include "matrix_view.cuh"
#include "../config.h"
#include "quant/qdq_2.cuh"
#include "quant/qdq_3.cuh"
#include "quant/qdq_4.cuh"
#include "quant/qdq_5.cuh"
#include "quant/qdq_6.cuh"
#include "quant/qdq_8.cuh"
#define GPTQ_BLOCK_KN_SIZE 128
#define GPTQ_BLOCK_M_SIZE_MAX 8
#... | text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/q_gemm.cu/0 | {
"file_path": "text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/q_gemm.cu",
"repo_id": "text-generation-inference",
"token_count": 3563
} | 210 |
import torch
import torch.distributed
from torch import nn
from transformers.activations import ACT2FN
from typing import Optional, List, Tuple
from text_generation_server.utils import paged_attention, flash_attn
from text_generation_server.utils.layers import (
TensorParallelRowLinear,
TensorParallelColumnLi... | text-generation-inference/server/text_generation_server/models/custom_modeling/flash_qwen2_modeling.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/models/custom_modeling/flash_qwen2_modeling.py",
"repo_id": "text-generation-inference",
"token_count": 6592
} | 211 |
import math
import os
import time
import itertools
import torch
import torch.distributed
import numpy as np
from loguru import logger
from dataclasses import dataclass
from opentelemetry import trace
from transformers import PreTrainedTokenizerBase
from typing import Optional, Tuple, List, Type, Dict
from text_gener... | text-generation-inference/server/text_generation_server/models/flash_causal_lm.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/models/flash_causal_lm.py",
"repo_id": "text-generation-inference",
"token_count": 23791
} | 212 |
import torch
import torch.distributed
from transformers import AutoTokenizer, PreTrainedTokenizerBase
from typing import Optional
import os
from text_generation_server.models.custom_modeling.mamba_modeling import (
MambaConfig,
)
from loguru import logger
from text_generation_server.pb import generate_pb2
from text... | text-generation-inference/server/text_generation_server/models/mamba.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/models/mamba.py",
"repo_id": "text-generation-inference",
"token_count": 14236
} | 213 |
import datetime
import torch
import os
from loguru import logger
from pathlib import Path
from safetensors.torch import save_file, load_file, _find_shared_tensors, _is_complete
from typing import List, Dict
from collections import defaultdict
def _remove_duplicate_names(
state_dict: Dict[str, torch.Tensor],
... | text-generation-inference/server/text_generation_server/utils/convert.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/utils/convert.py",
"repo_id": "text-generation-inference",
"token_count": 1769
} | 214 |
import re
from typing import List, Optional, Tuple
import math
import torch
from text_generation_server.pb import generate_pb2
from text_generation_server.pb.generate_pb2 import FinishReason, GrammarType
from text_generation_server.utils.logits_process import (
FrequencyPenaltyLogitsProcessor,
GrammarLogitProc... | text-generation-inference/server/text_generation_server/utils/tokens.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/utils/tokens.py",
"repo_id": "text-generation-inference",
"token_count": 10984
} | 215 |
.PHONY: style check-style test
DATA_DIR = data
dir_guard=@mkdir -p $(@D)
# Format source code automatically
style:
npm run lint
# Check the source code is formatted correctly
check-style:
npm run lint-check
TESTS_RESOURCES = $(DATA_DIR)/small.txt $(DATA_DIR)/roberta.json $(DATA_DIR)/tokenizer-wiki.json $(DATA_DI... | tokenizers/bindings/node/Makefile/0 | {
"file_path": "tokenizers/bindings/node/Makefile",
"repo_id": "tokenizers",
"token_count": 406
} | 216 |
import {
byteLevelPreTokenizer,
metaspacePreTokenizer,
punctuationPreTokenizer,
sequencePreTokenizer,
splitPreTokenizer,
whitespaceSplitPreTokenizer,
} from '../../'
describe('byteLevelPreTokenizer', () => {
it('instantiates correctly', () => {
const processor = byteLevelPreTokenizer()
expect(pro... | tokenizers/bindings/node/lib/bindings/pre-tokenizers.test.ts/0 | {
"file_path": "tokenizers/bindings/node/lib/bindings/pre-tokenizers.test.ts",
"repo_id": "tokenizers",
"token_count": 728
} | 217 |
{
"name": "tokenizers-linux-arm64-gnu",
"version": "0.13.4-rc1",
"os": [
"linux"
],
"cpu": [
"arm64"
],
"main": "tokenizers.linux-arm64-gnu.node",
"files": [
"tokenizers.linux-arm64-gnu.node"
],
"description": "Tokenizers platform specific bindings",
"keywords": [
"napi-rs",
"N... | tokenizers/bindings/node/npm/linux-arm64-gnu/package.json/0 | {
"file_path": "tokenizers/bindings/node/npm/linux-arm64-gnu/package.json",
"repo_id": "tokenizers",
"token_count": 289
} | 218 |
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::decoders::DecoderWrapper;
/// Decoder
#[derive(Clone, Serialize, Deserialize)]
#[napi]
pub struct Decoder {
#[serde(flatten, wi... | tokenizers/bindings/node/src/decoders.rs/0 | {
"file_path": "tokenizers/bindings/node/src/decoders.rs",
"repo_id": "tokenizers",
"token_count": 1821
} | 219 |
[target.x86_64-apple-darwin]
rustflags = [
"-C", "link-arg=-undefined",
"-C", "link-arg=dynamic_lookup",
"-C", "link-arg=-mmacosx-version-min=10.11",
]
[target.aarch64-apple-darwin]
rustflags = [
"-C", "link-arg=-undefined",
"-C", "link-arg=dynamic_lookup",
"-C", "link-arg=-mmacosx-version-min=10.11",
]
| tokenizers/bindings/python/.cargo/config.toml/0 | {
"file_path": "tokenizers/bindings/python/.cargo/config.toml",
"repo_id": "tokenizers",
"token_count": 146
} | 220 |
from .. import decoders
Decoder = decoders.Decoder
ByteLevel = decoders.ByteLevel
Replace = decoders.Replace
WordPiece = decoders.WordPiece
ByteFallback = decoders.ByteFallback
Fuse = decoders.Fuse
Strip = decoders.Strip
Metaspace = decoders.Metaspace
BPEDecoder = decoders.BPEDecoder
CTC = decoders.CTC
Sequence = dec... | tokenizers/bindings/python/py_src/tokenizers/decoders/__init__.py/0 | {
"file_path": "tokenizers/bindings/python/py_src/tokenizers/decoders/__init__.py",
"repo_id": "tokenizers",
"token_count": 128
} | 221 |
# Generated content DO NOT EDIT
class PostProcessor:
"""
Base class for all post-processors
This class is not supposed to be instantiated directly. Instead, any implementation of
a PostProcessor will return an instance of this class when instantiated.
"""
def num_special_tokens_to_add(self, is_... | tokenizers/bindings/python/py_src/tokenizers/processors/__init__.pyi/0 | {
"file_path": "tokenizers/bindings/python/py_src/tokenizers/processors/__init__.pyi",
"repo_id": "tokenizers",
"token_count": 4779
} | 222 |
use std::collections::HashMap;
use std::path::{Path, PathBuf};
use std::sync::{Arc, RwLock};
use crate::token::PyToken;
use crate::trainers::PyTrainer;
use pyo3::exceptions;
use pyo3::prelude::*;
use pyo3::types::*;
use serde::{Deserialize, Serialize};
use tk::models::bpe::{BpeBuilder, Merges, Vocab, BPE};
use tk::mod... | tokenizers/bindings/python/src/models.rs/0 | {
"file_path": "tokenizers/bindings/python/src/models.rs",
"repo_id": "tokenizers",
"token_count": 14445
} | 223 |
import json
import pickle
import pytest
from tokenizers.decoders import (
CTC,
BPEDecoder,
ByteLevel,
Decoder,
Metaspace,
Sequence,
WordPiece,
ByteFallback,
Replace,
Strip,
Fuse,
)
class TestByteLevel:
def test_instantiate(self):
assert ByteLevel() is not None... | tokenizers/bindings/python/tests/bindings/test_decoders.py/0 | {
"file_path": "tokenizers/bindings/python/tests/bindings/test_decoders.py",
"repo_id": "tokenizers",
"token_count": 3521
} | 224 |
from tokenizers import CharBPETokenizer
from ..utils import data_dir, multiprocessing_with_parallelism, openai_files
class TestCharBPETokenizer:
def test_basic_encode(self, openai_files):
tokenizer = CharBPETokenizer.from_file(openai_files["vocab"], openai_files["merges"])
output = tokenizer.enc... | tokenizers/bindings/python/tests/implementations/test_char_bpe.py/0 | {
"file_path": "tokenizers/bindings/python/tests/implementations/test_char_bpe.py",
"repo_id": "tokenizers",
"token_count": 1094
} | 225 |
# Tokenizer
<tokenizerslangcontent>
<python>
## Tokenizer
[[autodoc]] tokenizers.Tokenizer
- all
- decoder
- model
- normalizer
- padding
- post_processor
- pre_tokenizer
- truncation
</python>
<rust>
The Rust API Reference is available directly on the [Docs.rs](https://docs.rs/tokeniz... | tokenizers/docs/source-doc-builder/api/tokenizer.mdx/0 | {
"file_path": "tokenizers/docs/source-doc-builder/api/tokenizer.mdx",
"repo_id": "tokenizers",
"token_count": 156
} | 226 |
.highlight .c1, .highlight .sd{
color: #999
}
.highlight .nn, .highlight .k, .highlight .s1, .highlight .nb, .highlight .bp, .highlight .kc, .highlight .kt {
color: #FB8D68;
}
.highlight .kn, .highlight .nv, .highlight .s2, .highlight .ow, .highlight .kd, .highlight .kr, .highlight .s {
color: #6670FF;
}... | tokenizers/docs/source/_static/css/code-snippets.css/0 | {
"file_path": "tokenizers/docs/source/_static/css/code-snippets.css",
"repo_id": "tokenizers",
"token_count": 166
} | 227 |
Quicktour
====================================================================================================
Let's have a quick look at the 🤗 Tokenizers library features. The library provides an
implementation of today's most used tokenizers that is both easy to use and blazing fast.
.. only:: python
It can b... | tokenizers/docs/source/quicktour.rst/0 | {
"file_path": "tokenizers/docs/source/quicktour.rst",
"repo_id": "tokenizers",
"token_count": 8904
} | 228 |
<div align="center">
<h1><code>wasm-pack-template</code></h1>
<strong>A template for kick starting a Rust and WebAssembly project using <a href="https://github.com/rustwasm/wasm-pack">wasm-pack</a>.</strong>
<p>
<a href="https://travis-ci.org/rustwasm/wasm-pack-template"><img src="https://img.shields.io/tr... | tokenizers/tokenizers/examples/unstable_wasm/README.md/0 | {
"file_path": "tokenizers/tokenizers/examples/unstable_wasm/README.md",
"repo_id": "tokenizers",
"token_count": 811
} | 229 |
stable
| tokenizers/tokenizers/rust-toolchain/0 | {
"file_path": "tokenizers/tokenizers/rust-toolchain",
"repo_id": "tokenizers",
"token_count": 2
} | 230 |
use rand::distributions::WeightedIndex;
use rand::prelude::*;
use std::cell::RefCell;
use std::cmp::{min, Ordering};
use std::collections::BinaryHeap;
use std::rc::Rc;
type NodeRef = Rc<RefCell<Node>>;
type HypothesisRef = Rc<RefCell<Hypothesis>>;
type Agenda = BinaryHeap<Hypothesis>;
struct Hypothesis {
node_ref... | tokenizers/tokenizers/src/models/unigram/lattice.rs/0 | {
"file_path": "tokenizers/tokenizers/src/models/unigram/lattice.rs",
"repo_id": "tokenizers",
"token_count": 12682
} | 231 |
use crate::tokenizer::pattern::Pattern;
use crate::tokenizer::Decoder;
use crate::tokenizer::{NormalizedString, Normalizer, Result};
use crate::utils::SysRegex;
use serde::{Deserialize, Serialize};
/// Represents the different patterns that `Replace` can use
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize, Eq... | tokenizers/tokenizers/src/normalizers/replace.rs/0 | {
"file_path": "tokenizers/tokenizers/src/normalizers/replace.rs",
"repo_id": "tokenizers",
"token_count": 2048
} | 232 |
use regex::Regex;
use crate::tokenizer::{
pattern::Invert, PreTokenizedString, PreTokenizer, Result, SplitDelimiterBehavior,
};
use crate::utils::macro_rules_attribute;
#[derive(Clone, Debug, PartialEq, Eq)]
#[macro_rules_attribute(impl_serde_type!)]
pub struct Whitespace;
impl Default for Whitespace {
fn de... | tokenizers/tokenizers/src/pre_tokenizers/whitespace.rs/0 | {
"file_path": "tokenizers/tokenizers/src/pre_tokenizers/whitespace.rs",
"repo_id": "tokenizers",
"token_count": 1660
} | 233 |
//! This comes from the Rust libcore and is duplicated here because it is not exported
//! (cf <https://github.com/rust-lang/rust/blob/25091ed9b7739e12466fb2490baa1e8a2815121c/src/libcore/iter/adapters/mod.rs#L2664>)
//! We are now using the version from <https://stackoverflow.com/questions/44544323/how-to-unzip-a-sequ... | tokenizers/tokenizers/src/utils/iter.rs/0 | {
"file_path": "tokenizers/tokenizers/src/utils/iter.rs",
"repo_id": "tokenizers",
"token_count": 1339
} | 234 |
version: 2.1
setup: true
orbs:
continuation: circleci/continuation@0.1.0
parameters:
nightly:
type: boolean
default: false
jobs:
# Ensure running with CircleCI/huggingface
check_circleci_user:
docker:
- image: cimg/python:3.8.12
parallelism: 1
steps:... | transformers/.circleci/config.yml/0 | {
"file_path": "transformers/.circleci/config.yml",
"repo_id": "transformers",
"token_count": 5200
} | 235 |
# https://docs.nvidia.com/deeplearning/frameworks/pytorch-release-notes/rel-23-11.html#rel-23-11
FROM nvcr.io/nvidia/pytorch:23.04-py3
LABEL maintainer="Hugging Face"
ARG DEBIAN_FRONTEND=noninteractive
ARG PYTORCH='2.2.0'
# Example: `cu102`, `cu113`, etc.
ARG CUDA='cu121'
RUN apt -y update
RUN apt install -y libaio-... | transformers/docker/transformers-pytorch-deepspeed-latest-gpu/Dockerfile/0 | {
"file_path": "transformers/docker/transformers-pytorch-deepspeed-latest-gpu/Dockerfile",
"repo_id": "transformers",
"token_count": 890
} | 236 |
<!--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/de/add_new_pipeline.md/0 | {
"file_path": "transformers/docs/source/de/add_new_pipeline.md",
"repo_id": "transformers",
"token_count": 4595
} | 237 |
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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/transformers_agents.md/0 | {
"file_path": "transformers/docs/source/de/transformers_agents.md",
"repo_id": "transformers",
"token_count": 6629
} | 238 |
<!--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/create_a_model.md/0 | {
"file_path": "transformers/docs/source/en/create_a_model.md",
"repo_id": "transformers",
"token_count": 5528
} | 239 |
<!--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/auto.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/auto.md",
"repo_id": "transformers",
"token_count": 2622
} | 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 agreed... | transformers/docs/source/en/model_doc/blenderbot.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/blenderbot.md",
"repo_id": "transformers",
"token_count": 1405
} | 241 |
<!--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/encoder-decoder.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/encoder-decoder.md",
"repo_id": "transformers",
"token_count": 2664
} | 242 |
<!--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/imagegpt.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/imagegpt.md",
"repo_id": "transformers",
"token_count": 1915
} | 243 |
<!--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
} | 244 |
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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/musicgen_melody.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/musicgen_melody.md",
"repo_id": "transformers",
"token_count": 4090
} | 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/model_doc/pegasus.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/pegasus.md",
"repo_id": "transformers",
"token_count": 1966
} | 246 |
<!--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/realm.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/realm.md",
"repo_id": "transformers",
"token_count": 926
} | 247 |
<!--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/sew-d.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/sew-d.md",
"repo_id": "transformers",
"token_count": 732
} | 248 |
<!--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/unispeech-sat.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/unispeech-sat.md",
"repo_id": "transformers",
"token_count": 1045
} | 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/xlnet.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/xlnet.md",
"repo_id": "transformers",
"token_count": 2042
} | 250 |
<!--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/run_scripts.md/0 | {
"file_path": "transformers/docs/source/en/run_scripts.md",
"repo_id": "transformers",
"token_count": 5916
} | 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/tasks/monocular_depth_estimation.md/0 | {
"file_path": "transformers/docs/source/en/tasks/monocular_depth_estimation.md",
"repo_id": "transformers",
"token_count": 1553
} | 252 |
<!--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/testing.md/0 | {
"file_path": "transformers/docs/source/en/testing.md",
"repo_id": "transformers",
"token_count": 13408
} | 253 |
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | transformers/docs/source/es/chat_templating.md/0 | {
"file_path": "transformers/docs/source/es/chat_templating.md",
"repo_id": "transformers",
"token_count": 8911
} | 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/es/pipeline_tutorial.md/0 | {
"file_path": "transformers/docs/source/es/pipeline_tutorial.md",
"repo_id": "transformers",
"token_count": 2294
} | 255 |
<!--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/it/add_new_pipeline.md/0 | {
"file_path": "transformers/docs/source/it/add_new_pipeline.md",
"repo_id": "transformers",
"token_count": 4132
} | 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/it/perf_infer_gpu_one.md/0 | {
"file_path": "transformers/docs/source/it/perf_infer_gpu_one.md",
"repo_id": "transformers",
"token_count": 2306
} | 257 |
<!--
Copyright 2023 The HuggingFace Team. All rights reserved.
ライセンス:Apache License、バージョン2.0(「ライセンス」)に基づいています。このファイルは、ライセンスに準拠していない限り、使用できません。ライセンスのコピーは以下から入手できます:
http://www.apache.org/licenses/LICENSE-2.0
適用法に従って必要な場合、または書面で同意した場合を除き、ライセンスの下で配布されるソフトウェアは、「AS IS」の基盤で、明示または黙示を問わず、いかなる保証や条件も含みません。ライセンスの詳細については、ライセンス文... | transformers/docs/source/ja/add_tensorflow_model.md/0 | {
"file_path": "transformers/docs/source/ja/add_tensorflow_model.md",
"repo_id": "transformers",
"token_count": 11998
} | 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 ... | transformers/docs/source/ja/installation.md/0 | {
"file_path": "transformers/docs/source/ja/installation.md",
"repo_id": "transformers",
"token_count": 4808
} | 259 |
<!--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/altclip.md/0 | {
"file_path": "transformers/docs/source/ja/model_doc/altclip.md",
"repo_id": "transformers",
"token_count": 2400
} | 260 |
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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/bit.md/0 | {
"file_path": "transformers/docs/source/ja/model_doc/bit.md",
"repo_id": "transformers",
"token_count": 1858
} | 261 |
<!--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/clvp.md/0 | {
"file_path": "transformers/docs/source/ja/model_doc/clvp.md",
"repo_id": "transformers",
"token_count": 2038
} | 262 |
<!--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/deit.md/0 | {
"file_path": "transformers/docs/source/ja/model_doc/deit.md",
"repo_id": "transformers",
"token_count": 3682
} | 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 agree... | transformers/docs/source/ja/quicktour.md/0 | {
"file_path": "transformers/docs/source/ja/quicktour.md",
"repo_id": "transformers",
"token_count": 13065
} | 264 |
<!--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
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Unless required by applicable law or agreed... | transformers/docs/source/ja/tasks/object_detection.md/0 | {
"file_path": "transformers/docs/source/ja/tasks/object_detection.md",
"repo_id": "transformers",
"token_count": 12769
} | 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 ... | transformers/docs/source/ko/model_memory_anatomy.md/0 | {
"file_path": "transformers/docs/source/ko/model_memory_anatomy.md",
"repo_id": "transformers",
"token_count": 8877
} | 266 |
<!--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/philosophy.md/0 | {
"file_path": "transformers/docs/source/ko/philosophy.md",
"repo_id": "transformers",
"token_count": 5165
} | 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
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Unless required by applicable law or agreed... | transformers/docs/source/ko/tf_xla.md/0 | {
"file_path": "transformers/docs/source/ko/tf_xla.md",
"repo_id": "transformers",
"token_count": 6235
} | 268 |
<!--版权2023年HuggingFace团队保留所有权利。
根据Apache许可证第2.0版(“许可证”)许可;除非符合许可证,否则您不得使用此文件。您可以在以下网址获取许可证的副本:
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除非适用法律要求或书面同意,否则按“按原样”分发的软件,无论是明示还是暗示的,都没有任何担保或条件。请参阅许可证以了解特定语言下的权限和限制。
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# 🤗 加速分布式训练
... | transformers/docs/source/zh/accelerate.md/0 | {
"file_path": "transformers/docs/source/zh/accelerate.md",
"repo_id": "transformers",
"token_count": 2552
} | 269 |
<!--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/internal/generation_utils.md/0 | {
"file_path": "transformers/docs/source/zh/internal/generation_utils.md",
"repo_id": "transformers",
"token_count": 3487
} | 270 |
<!--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/main_classes/logging.md/0 | {
"file_path": "transformers/docs/source/zh/main_classes/logging.md",
"repo_id": "transformers",
"token_count": 2154
} | 271 |
<!---
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 ... | transformers/examples/flax/speech-recognition/README.md/0 | {
"file_path": "transformers/examples/flax/speech-recognition/README.md",
"repo_id": "transformers",
"token_count": 1039
} | 272 |
# 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/question-answering/run_squad_trainer.py/0 | {
"file_path": "transformers/examples/legacy/question-answering/run_squad_trainer.py",
"repo_id": "transformers",
"token_count": 2569
} | 273 |
# Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | transformers/examples/legacy/seq2seq/old_test_datasets.py/0 | {
"file_path": "transformers/examples/legacy/seq2seq/old_test_datasets.py",
"repo_id": "transformers",
"token_count": 5152
} | 274 |
# 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/seq2seq_training_args.py/0 | {
"file_path": "transformers/examples/legacy/seq2seq/seq2seq_training_args.py",
"repo_id": "transformers",
"token_count": 888
} | 275 |
#!/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/pytorch/question-answering/run_seq2seq_qa.py/0 | {
"file_path": "transformers/examples/pytorch/question-answering/run_seq2seq_qa.py",
"repo_id": "transformers",
"token_count": 13528
} | 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 applicable law or ... | transformers/examples/pytorch/summarization/README.md/0 | {
"file_path": "transformers/examples/pytorch/summarization/README.md",
"repo_id": "transformers",
"token_count": 2636
} | 277 |
<!---
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/pytorch/token-classification/README.md/0 | {
"file_path": "transformers/examples/pytorch/token-classification/README.md",
"repo_id": "transformers",
"token_count": 1442
} | 278 |
# Patience-based Early Exit
Patience-based Early Exit (PABEE) is a plug-and-play inference method for pretrained language models.
We have already implemented it on BERT and ALBERT. Basically, you can make your LM faster and more robust with PABEE. It can even improve the performance of ALBERT on GLUE. The only sacrifi... | transformers/examples/research_projects/bert-loses-patience/README.md/0 | {
"file_path": "transformers/examples/research_projects/bert-loses-patience/README.md",
"repo_id": "transformers",
"token_count": 1329
} | 279 |
# coding=utf-8
# Copyright 2019-present, the HuggingFace Inc. team and Facebook, 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
#
# Un... | transformers/examples/research_projects/distillation/distiller.py/0 | {
"file_path": "transformers/examples/research_projects/distillation/distiller.py",
"repo_id": "transformers",
"token_count": 12494
} | 280 |
<p align="center"> <img src="http://sayef.tech:8082/uploads/FSNER-LOGO-2.png" alt="FSNER LOGO"> </p>
<p align="center">
Implemented by <a href="https://huggingface.co/sayef"> sayef </a>.
</p>
## Overview
The FSNER model was proposed in [Example-Based Named Entity Recognition](https://arxiv.org/abs/2008.10570) by ... | transformers/examples/research_projects/fsner/README.md/0 | {
"file_path": "transformers/examples/research_projects/fsner/README.md",
"repo_id": "transformers",
"token_count": 1174
} | 281 |
import json
import os
from dataclasses import dataclass
from functools import partial
from typing import Callable
import flax.linen as nn
import jax
import jax.numpy as jnp
import joblib
import optax
import wandb
from flax import jax_utils, struct, traverse_util
from flax.serialization import from_bytes, to_bytes
from... | transformers/examples/research_projects/jax-projects/big_bird/bigbird_flax.py/0 | {
"file_path": "transformers/examples/research_projects/jax-projects/big_bird/bigbird_flax.py",
"repo_id": "transformers",
"token_count": 5480
} | 282 |
# Wav2Vec2 Contrastive Loss PreTraining examples
The following example showcases how to pretrain a wav2vec2 model using the JAX/Flax backend.
Pretraining Wav2Vec2 is rather complex, so it is highly recommended to read the
[official paper](https://arxiv.org/abs/2006.11477).
JAX/Flax allows you to trace pure functions... | transformers/examples/research_projects/jax-projects/wav2vec2/README.md/0 | {
"file_path": "transformers/examples/research_projects/jax-projects/wav2vec2/README.md",
"repo_id": "transformers",
"token_count": 1507
} | 283 |
"""
coding=utf-8
Copyright 2018, Antonio Mendoza Hao Tan, Mohit Bansal
Adapted From Facebook Inc, Detectron2
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/license... | transformers/examples/research_projects/lxmert/processing_image.py/0 | {
"file_path": "transformers/examples/research_projects/lxmert/processing_image.py",
"repo_id": "transformers",
"token_count": 2793
} | 284 |
# 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/research_projects/movement-pruning/emmental/configuration_bert_masked.py/0 | {
"file_path": "transformers/examples/research_projects/movement-pruning/emmental/configuration_bert_masked.py",
"repo_id": "transformers",
"token_count": 995
} | 285 |
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