text stringlengths 96 319k | id stringlengths 14 178 | metadata dict |
|---|---|---|
# coding=utf-8
# Copyright 2025 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable... | diffusers/utils/check_doc_toc.py/0 | {
"file_path": "diffusers/utils/check_doc_toc.py",
"repo_id": "diffusers",
"token_count": 2177
} |
# Copyright 2024 The HuggingFace Team, the AllenNLP library authors. 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
#
... | diffusers/utils/stale.py/0 | {
"file_path": "diffusers/utils/stale.py",
"repo_id": "diffusers",
"token_count": 1008
} |
This tutorial explains how to use [Stretch 3](https://hello-robot.com/stretch-3-product) with LeRobot.
## Setup
Familiarize yourself with Stretch by following its [tutorials](https://docs.hello-robot.com/0.3/getting_started/hello_robot/) (recommended).
To use LeRobot on Stretch, 3 options are available:
- [tethered ... | lerobot/examples/8_use_stretch.md/0 | {
"file_path": "lerobot/examples/8_use_stretch.md",
"repo_id": "lerobot",
"token_count": 2135
} |
#!/usr/bin/env python
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# ... | lerobot/lerobot/common/datasets/push_dataset_to_hub/pusht_zarr_format.py/0 | {
"file_path": "lerobot/lerobot/common/datasets/push_dataset_to_hub/pusht_zarr_format.py",
"repo_id": "lerobot",
"token_count": 4650
} |
#!/usr/bin/env python
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# ... | lerobot/lerobot/common/optim/factory.py/0 | {
"file_path": "lerobot/lerobot/common/optim/factory.py",
"repo_id": "lerobot",
"token_count": 883
} |
#!/usr/bin/env python
# Copyright 2025 Physical Intelligence and The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org... | lerobot/lerobot/common/policies/pi0/modeling_pi0.py/0 | {
"file_path": "lerobot/lerobot/common/policies/pi0/modeling_pi0.py",
"repo_id": "lerobot",
"token_count": 12336
} |
import enum
import logging
import math
import time
import traceback
from copy import deepcopy
import numpy as np
import tqdm
from lerobot.common.robot_devices.motors.configs import DynamixelMotorsBusConfig
from lerobot.common.robot_devices.utils import RobotDeviceAlreadyConnectedError, RobotDeviceNotConnectedError
fr... | lerobot/lerobot/common/robot_devices/motors/dynamixel.py/0 | {
"file_path": "lerobot/lerobot/common/robot_devices/motors/dynamixel.py",
"repo_id": "lerobot",
"token_count": 15815
} |
import datetime as dt
import logging
from dataclasses import dataclass, field
from pathlib import Path
from lerobot.common import envs, policies # noqa: F401
from lerobot.common.utils.utils import auto_select_torch_device, is_amp_available, is_torch_device_available
from lerobot.configs import parser
from lerobot.con... | lerobot/lerobot/configs/eval.py/0 | {
"file_path": "lerobot/lerobot/configs/eval.py",
"repo_id": "lerobot",
"token_count": 1574
} |
#!/usr/bin/env python
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# ... | lerobot/lerobot/scripts/visualize_image_transforms.py/0 | {
"file_path": "lerobot/lerobot/scripts/visualize_image_transforms.py",
"repo_id": "lerobot",
"token_count": 1939
} |
#!/usr/bin/env python
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# ... | lerobot/tests/scripts/save_image_transforms_to_safetensors.py/0 | {
"file_path": "lerobot/tests/scripts/save_image_transforms_to_safetensors.py",
"repo_id": "lerobot",
"token_count": 1043
} |
#!/usr/bin/env python
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# ... | lerobot/tests/test_sampler.py/0 | {
"file_path": "lerobot/tests/test_sampler.py",
"repo_id": "lerobot",
"token_count": 1429
} |
[isort]
default_section = FIRSTPARTY
ensure_newline_before_comments = True
force_grid_wrap = 0
include_trailing_comma = True
known_first_party = open_r1
known_third_party =
transformers
datasets
fugashi
git
h5py
matplotlib
nltk
numpy
packaging
pandas
psutil
pytest
rou... | open-r1/setup.cfg/0 | {
"file_path": "open-r1/setup.cfg",
"repo_id": "open-r1",
"token_count": 300
} |
# coding=utf-8
# Copyright 2025 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... | open-r1/src/open_r1/utils/upload_details.py/0 | {
"file_path": "open-r1/src/open_r1/utils/upload_details.py",
"repo_id": "open-r1",
"token_count": 615
} |
<!--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... | peft/docs/source/package_reference/lora.md/0 | {
"file_path": "peft/docs/source/package_reference/lora.md",
"repo_id": "peft",
"token_count": 627
} |
<!--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... | peft/docs/source/task_guides/lora_based_methods.md/0 | {
"file_path": "peft/docs/source/task_guides/lora_based_methods.md",
"repo_id": "peft",
"token_count": 4895
} |
# 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 applicabl... | peft/examples/boft_controlnet/utils/light_controlnet.py/0 | {
"file_path": "peft/examples/boft_controlnet/utils/light_controlnet.py",
"repo_id": "peft",
"token_count": 4318
} |
# Copyright 2023-present the HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or... | peft/examples/bone_finetuning/bone_finetuning.py/0 | {
"file_path": "peft/examples/bone_finetuning/bone_finetuning.py",
"repo_id": "peft",
"token_count": 1490
} |
import os
import torch
from accelerate import Accelerator
from datasets import load_dataset
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer, default_data_collator, get_linear_schedule_with_warmup
from peft import LoraConfig, TaskType, get_pef... | peft/examples/conditional_generation/peft_lora_seq2seq_accelerate_fsdp.py/0 | {
"file_path": "peft/examples/conditional_generation/peft_lora_seq2seq_accelerate_fsdp.py",
"repo_id": "peft",
"token_count": 2543
} |
# Copyright 2023-present the HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or... | peft/examples/pissa_finetuning/pissa_finetuning.py/0 | {
"file_path": "peft/examples/pissa_finetuning/pissa_finetuning.py",
"repo_id": "peft",
"token_count": 2492
} |
import os
from enum import Enum
import packaging.version
import torch
import transformers
from datasets import DatasetDict, load_dataset, load_from_disk
from datasets.builder import DatasetGenerationError
from transformers import (
AutoModelForCausalLM,
AutoTokenizer,
BitsAndBytesConfig,
)
from peft impor... | peft/examples/sft/utils.py/0 | {
"file_path": "peft/examples/sft/utils.py",
"repo_id": "peft",
"token_count": 3623
} |
# Copyright 2023-present the HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or... | peft/src/peft/auto.py/0 | {
"file_path": "peft/src/peft/auto.py",
"repo_id": "peft",
"token_count": 2874
} |
# Copyright 2023-present the HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or... | peft/src/peft/tuners/adalora/gptq.py/0 | {
"file_path": "peft/src/peft/tuners/adalora/gptq.py",
"repo_id": "peft",
"token_count": 1154
} |
# Copyright 2024-present the HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or... | peft/src/peft/tuners/bone/config.py/0 | {
"file_path": "peft/src/peft/tuners/bone/config.py",
"repo_id": "peft",
"token_count": 2283
} |
# Copyright 2023-present the HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or... | peft/src/peft/tuners/ia3/config.py/0 | {
"file_path": "peft/src/peft/tuners/ia3/config.py",
"repo_id": "peft",
"token_count": 2119
} |
# Copyright 2024-present the HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or... | peft/src/peft/tuners/lora/aqlm.py/0 | {
"file_path": "peft/src/peft/tuners/lora/aqlm.py",
"repo_id": "peft",
"token_count": 1647
} |
# Copyright 2023-present the HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or... | peft/src/peft/tuners/mixed/model.py/0 | {
"file_path": "peft/src/peft/tuners/mixed/model.py",
"repo_id": "peft",
"token_count": 6670
} |
# Copyright 2023-present the HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or... | peft/tests/test_hub_features.py/0 | {
"file_path": "peft/tests/test_hub_features.py",
"repo_id": "peft",
"token_count": 1945
} |
# Copyright 2024-present the HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or... | peft/tests/test_vera.py/0 | {
"file_path": "peft/tests/test_vera.py",
"repo_id": "peft",
"token_count": 5925
} |
# PyTorch Image Models
- [What's New](#whats-new)
- [Introduction](#introduction)
- [Models](#models)
- [Features](#features)
- [Results](#results)
- [Getting Started (Documentation)](#getting-started-documentation)
- [Train, Validation, Inference Scripts](#train-validation-inference-scripts)
- [Awesome PyTorch Resourc... | pytorch-image-models/README.md/0 | {
"file_path": "pytorch-image-models/README.md",
"repo_id": "pytorch-image-models",
"token_count": 21449
} |
# Model Summaries
The model architectures included come from a wide variety of sources. Sources, including papers, original impl ("reference code") that I rewrote / adapted, and PyTorch impl that I leveraged directly ("code") are listed below.
Most included models have pretrained weights. The weights are either:
1. ... | pytorch-image-models/hfdocs/source/models.mdx/0 | {
"file_path": "pytorch-image-models/hfdocs/source/models.mdx",
"repo_id": "pytorch-image-models",
"token_count": 4501
} |
# MobileNet v2
**MobileNetV2** is a convolutional neural network architecture that seeks to perform well on mobile devices. It is based on an [inverted residual structure](https://paperswithcode.com/method/inverted-residual-block) where the residual connections are between the bottleneck layers. The intermediate expa... | pytorch-image-models/hfdocs/source/models/mobilenet-v2.mdx/0 | {
"file_path": "pytorch-image-models/hfdocs/source/models/mobilenet-v2.mdx",
"repo_id": "pytorch-image-models",
"token_count": 3403
} |
# Quickstart
This quickstart is intended for developers who are ready to dive into the code and see an example of how to integrate `timm` into their model training workflow.
First, you'll need to install `timm`. For more information on installation, see [Installation](installation).
```bash
pip install timm
```
## ... | pytorch-image-models/hfdocs/source/quickstart.mdx/0 | {
"file_path": "pytorch-image-models/hfdocs/source/quickstart.mdx",
"repo_id": "pytorch-image-models",
"token_count": 2581
} |
import os
import pickle
def load_class_map(map_or_filename, root=''):
if isinstance(map_or_filename, dict):
assert dict, 'class_map dict must be non-empty'
return map_or_filename
class_map_path = map_or_filename
if not os.path.exists(class_map_path):
class_map_path = os.path.join(r... | pytorch-image-models/timm/data/readers/class_map.py/0 | {
"file_path": "pytorch-image-models/timm/data/readers/class_map.py",
"repo_id": "pytorch-image-models",
"token_count": 387
} |
from .activations import *
from .adaptive_avgmax_pool import \
adaptive_avgmax_pool2d, select_adaptive_pool2d, AdaptiveAvgMaxPool2d, SelectAdaptivePool2d
from .attention2d import MultiQueryAttention2d, Attention2d, MultiQueryAttentionV2
from .attention_pool import AttentionPoolLatent
from .attention_pool2d import A... | pytorch-image-models/timm/layers/__init__.py/0 | {
"file_path": "pytorch-image-models/timm/layers/__init__.py",
"repo_id": "pytorch-image-models",
"token_count": 1500
} |
""" Attention Factory
Hacked together by / Copyright 2021 Ross Wightman
"""
import torch
from functools import partial
from .bottleneck_attn import BottleneckAttn
from .cbam import CbamModule, LightCbamModule
from .eca import EcaModule, CecaModule
from .gather_excite import GatherExcite
from .global_context import Gl... | pytorch-image-models/timm/layers/create_attn.py/0 | {
"file_path": "pytorch-image-models/timm/layers/create_attn.py",
"repo_id": "pytorch-image-models",
"token_count": 1588
} |
""" Image to Patch Hybird Embedding Layer
Hacked together by / Copyright 2020 Ross Wightman
"""
import logging
import math
from typing import List, Optional, Tuple, Union
import torch
from torch import nn as nn
import torch.nn.functional as F
from .format import Format, nchw_to
from .helpers import to_2tuple
from .p... | pytorch-image-models/timm/layers/hybrid_embed.py/0 | {
"file_path": "pytorch-image-models/timm/layers/hybrid_embed.py",
"repo_id": "pytorch-image-models",
"token_count": 5059
} |
""" AvgPool2d 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 List, Tuple, Optional
from .helpers import to_2tuple
from .padding import pad_same, get_padding_value
def avg_pool2d_same(x, kernel_size: List[int... | pytorch-image-models/timm/layers/pool2d_same.py/0 | {
"file_path": "pytorch-image-models/timm/layers/pool2d_same.py",
"repo_id": "pytorch-image-models",
"token_count": 1294
} |
import torch
import torch.nn as nn
class AsymmetricLossMultiLabel(nn.Module):
def __init__(self, gamma_neg=4, gamma_pos=1, clip=0.05, eps=1e-8, disable_torch_grad_focal_loss=False):
super(AsymmetricLossMultiLabel, self).__init__()
self.gamma_neg = gamma_neg
self.gamma_pos = gamma_pos
... | pytorch-image-models/timm/loss/asymmetric_loss.py/0 | {
"file_path": "pytorch-image-models/timm/loss/asymmetric_loss.py",
"repo_id": "pytorch-image-models",
"token_count": 1616
} |
""" DaViT: Dual Attention Vision Transformers
As described in https://arxiv.org/abs/2204.03645
Input size invariant transformer architecture that combines channel and spacial
attention in each block. The attention mechanisms used are linear in complexity.
DaViT model defs and weights adapted from https://github.com/... | pytorch-image-models/timm/models/davit.py/0 | {
"file_path": "pytorch-image-models/timm/models/davit.py",
"repo_id": "pytorch-image-models",
"token_count": 14224
} |
"""
MambaOut models for image classification.
Some implementations are modified from:
timm (https://github.com/rwightman/pytorch-image-models),
MetaFormer (https://github.com/sail-sg/metaformer),
InceptionNeXt (https://github.com/sail-sg/inceptionnext)
"""
from collections import OrderedDict
from typing import Optional... | pytorch-image-models/timm/models/mambaout.py/0 | {
"file_path": "pytorch-image-models/timm/models/mambaout.py",
"repo_id": "pytorch-image-models",
"token_count": 10626
} |
"""RegNet X, Y, Z, and more
Paper: `Designing Network Design Spaces` - https://arxiv.org/abs/2003.13678
Original Impl: https://github.com/facebookresearch/pycls/blob/master/pycls/models/regnet.py
Paper: `Fast and Accurate Model Scaling` - https://arxiv.org/abs/2103.06877
Original Impl: None
Based on original PyTorch... | pytorch-image-models/timm/models/regnet.py/0 | {
"file_path": "pytorch-image-models/timm/models/regnet.py",
"repo_id": "pytorch-image-models",
"token_count": 22592
} |
""" Transformer in Transformer (TNT) in PyTorch
A PyTorch implement of TNT as described in
'Transformer in Transformer' - https://arxiv.org/abs/2103.00112
The official mindspore code is released and available at
https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/TNT
"""
import math
from typing im... | pytorch-image-models/timm/models/tnt.py/0 | {
"file_path": "pytorch-image-models/timm/models/tnt.py",
"repo_id": "pytorch-image-models",
"token_count": 6783
} |
""" Optimizer Factory w/ custom Weight Decay & Layer Decay support
Hacked together by / Copyright 2021 Ross Wightman
"""
import logging
from dataclasses import dataclass
from functools import partial
from typing import Any, Callable, Dict, List, Optional, Set, Tuple, Type, Union
from fnmatch import fnmatch
import impo... | pytorch-image-models/timm/optim/_optim_factory.py/0 | {
"file_path": "pytorch-image-models/timm/optim/_optim_factory.py",
"repo_id": "pytorch-image-models",
"token_count": 18438
} |
""" Lookahead Optimizer Wrapper.
Implementation modified from: https://github.com/alphadl/lookahead.pytorch
Paper: `Lookahead Optimizer: k steps forward, 1 step back` - https://arxiv.org/abs/1907.08610
Hacked together by / Copyright 2020 Ross Wightman
"""
from collections import OrderedDict
from typing import Callable... | pytorch-image-models/timm/optim/lookahead.py/0 | {
"file_path": "pytorch-image-models/timm/optim/lookahead.py",
"repo_id": "pytorch-image-models",
"token_count": 1134
} |
""" 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
} |
<!---
Copyright 2025 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 ... | smolagents/CONTRIBUTING.md/0 | {
"file_path": "smolagents/CONTRIBUTING.md",
"repo_id": "smolagents",
"token_count": 1156
} |
<!--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... | smolagents/docs/source/en/reference/agents.md/0 | {
"file_path": "smolagents/docs/source/en/reference/agents.md",
"repo_id": "smolagents",
"token_count": 573
} |
<!--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... | smolagents/docs/source/hi/reference/agents.md/0 | {
"file_path": "smolagents/docs/source/hi/reference/agents.md",
"repo_id": "smolagents",
"token_count": 4332
} |
<!--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... | smolagents/docs/source/zh/reference/tools.md/0 | {
"file_path": "smolagents/docs/source/zh/reference/tools.md",
"repo_id": "smolagents",
"token_count": 704
} |
#!/usr/bin/env python
# coding=utf-8
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/L... | smolagents/src/smolagents/agents.py/0 | {
"file_path": "smolagents/src/smolagents/agents.py",
"repo_id": "smolagents",
"token_count": 18519
} |
from unittest.mock import patch
import pytest
from smolagents.agents import MultiStepAgent
from smolagents.monitoring import LogLevel
original_multi_step_agent_init = MultiStepAgent.__init__
@pytest.fixture(autouse=True)
def patch_multi_step_agent_with_suppressed_logging():
with patch.object(MultiStepAgent, "... | smolagents/tests/conftest.py/0 | {
"file_path": "smolagents/tests/conftest.py",
"repo_id": "smolagents",
"token_count": 230
} |
# coding=utf-8
# Copyright 2024 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 ag... | smolagents/tests/test_utils.py/0 | {
"file_path": "smolagents/tests/test_utils.py",
"repo_id": "smolagents",
"token_count": 4135
} |
[package]
name = "text-generation-backends-trtllm"
version.workspace = true
edition.workspace = true
authors.workspace = true
homepage.workspace = true
[dependencies]
async-trait = "0.1"
clap = { version = "4.5", features = ["derive"] }
cxx = "1.0"
hashbrown = "0.15"
hf-hub = { workspace = true }
text-generation-route... | text-generation-inference/backends/trtllm/Cargo.toml/0 | {
"file_path": "text-generation-inference/backends/trtllm/Cargo.toml",
"repo_id": "text-generation-inference",
"token_count": 275
} |
use std::path::{Path, PathBuf};
use clap::Parser;
use hf_hub::api::tokio::{Api, ApiBuilder};
use hf_hub::{Cache, Repo, RepoType};
use tracing::info;
use text_generation_backends_trtllm::errors::TensorRtLlmBackendError;
use text_generation_backends_trtllm::TensorRtLlmBackendV2;
use text_generation_router::server::{
... | text-generation-inference/backends/trtllm/src/main.rs/0 | {
"file_path": "text-generation-inference/backends/trtllm/src/main.rs",
"repo_id": "text-generation-inference",
"token_count": 5530
} |
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": 2288
} |
from enum import Enum
from pydantic import BaseModel, field_validator, ConfigDict
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(BaseM... | 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": 5255
} |
# Guidance
Text Generation Inference (TGI) now supports [JSON and regex grammars](#grammar-and-constraints) and [tools and functions](#tools-and-functions) to help developers guide LLM responses to fit their needs.
These feature are available starting from version `1.4.3`. They are accessible via the [`huggingface_hu... | text-generation-inference/docs/source/basic_tutorials/using_guidance.md/0 | {
"file_path": "text-generation-inference/docs/source/basic_tutorials/using_guidance.md",
"repo_id": "text-generation-inference",
"token_count": 6730
} |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [],
"seed": 0,
"tokens": [
{
"id": 5267,
"logprob": -1.1464844,
"special": false,
"text": "?\n"
},
{
"id": 33464,
"logprob":... | text-generation-inference/integration-tests/models/__snapshots__/test_compressed_tensors_w8a8_int_dynamic_weight/test_compressed_tensors_w8a8_int_dynamic_weight_all_params.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_compressed_tensors_w8a8_int_dynamic_weight/test_compressed_tensors_w8a8_int_dynamic_weight_all_params.json",
"repo_id": "text-generation-inference",
"token_count": 862
} |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [],
"seed": null,
"tokens": [
{
"id": 198,
"logprob": -0.68603516,
"special": false,
"text": "\n"
},
{
"id": 198,
"logprob":... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_gpt2/test_flash_gpt2.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_gpt2/test_flash_gpt2.json",
"repo_id": "text-generation-inference",
"token_count": 866
} |
{
"choices": [
{
"delta": {
"content": "",
"role": "assistant",
"tool_calls": null
},
"finish_reason": "stop",
"index": 0,
"logprobs": null
}
],
"created": 1737646031,
"id": "",
"model": "Qwen/Qwen2-VL-7B-Instruct",
"object": "chat.completion.chu... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_qwen2_vl/test_flash_qwen2_vl_simple_streaming.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_qwen2_vl/test_flash_qwen2_vl_simple_streaming.json",
"repo_id": "text-generation-inference",
"token_count": 201
} |
{
"details": {
"best_of_sequences": null,
"finish_reason": "eos_token",
"generated_tokens": 30,
"prefill": [],
"seed": null,
"tokens": [
{
"id": 6377,
"logprob": -0.14916992,
"special": false,
"text": "{\""
},
{
"id": 29888,
"lo... | text-generation-inference/integration-tests/models/__snapshots__/test_grammar_llama/test_non_flash_llama_grammar_json.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_grammar_llama/test_non_flash_llama_grammar_json.json",
"repo_id": "text-generation-inference",
"token_count": 2413
} |
{
"details": {
"finish_reason": "length",
"generated_tokens": 40,
"prefill": [],
"seed": null,
"tokens": [
{
"id": 13,
"logprob": -0.31347656,
"special": false,
"text": "\n"
},
{
"id": 13,
"logprob": -0.27441406,
"special": ... | text-generation-inference/integration-tests/models/__snapshots__/test_lora_mistral/test_lora_mistral_without_customer_support_adapter.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_lora_mistral/test_lora_mistral_without_customer_support_adapter.json",
"repo_id": "text-generation-inference",
"token_count": 3126
} |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [],
"seed": 0,
"tokens": [
{
"id": 29899,
"logprob": -1.4980469,
"special": false,
"text": "-"
},
{
"id": 1454,
"logprob": -... | text-generation-inference/integration-tests/models/__snapshots__/test_server_gptq_quantized/test_server_gptq_quantized_all_params.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_server_gptq_quantized/test_server_gptq_quantized_all_params.json",
"repo_id": "text-generation-inference",
"token_count": 853
} |
import pytest
@pytest.fixture(scope="module")
def bloom_560m_sharded_handle(launcher):
with launcher("bigscience/bloom-560m", num_shard=2) as handle:
yield handle
@pytest.fixture(scope="module")
async def bloom_560m_sharded(bloom_560m_sharded_handle):
await bloom_560m_sharded_handle.health(240)
... | text-generation-inference/integration-tests/models/test_bloom_560m_sharded.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_bloom_560m_sharded.py",
"repo_id": "text-generation-inference",
"token_count": 527
} |
import pytest
@pytest.fixture(scope="module")
def flash_gpt2_handle(launcher):
with launcher("openai-community/gpt2", num_shard=2) as handle:
yield handle
@pytest.fixture(scope="module")
async def flash_gpt2(flash_gpt2_handle):
await flash_gpt2_handle.health(300)
return flash_gpt2_handle.client
... | text-generation-inference/integration-tests/models/test_flash_gpt2.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_flash_gpt2.py",
"repo_id": "text-generation-inference",
"token_count": 476
} |
import pytest
@pytest.fixture(scope="module")
def flash_neox_handle(launcher):
with launcher("stabilityai/stablelm-tuned-alpha-3b", num_shard=1) as handle:
yield handle
@pytest.fixture(scope="module")
async def flash_neox(flash_neox_handle):
await flash_neox_handle.health(300)
return flash_neox_... | text-generation-inference/integration-tests/models/test_flash_neox.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_flash_neox.py",
"repo_id": "text-generation-inference",
"token_count": 514
} |
import pytest
@pytest.fixture(scope="module")
def flash_idefics2_next_handle(launcher):
with launcher(
"HuggingFaceM4/idefics2-8b",
) as handle:
yield handle
@pytest.fixture(scope="module")
async def flash_idefics2_next(flash_idefics2_next_handle):
await flash_idefics2_next_handle.health... | text-generation-inference/integration-tests/models/test_idefics2.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_idefics2.py",
"repo_id": "text-generation-inference",
"token_count": 1159
} |
[tool.poetry]
name = "text-generation-inference-benchmarks"
version = "0.1.0"
description = ""
authors = ["Hugo Larcher <hugo.larcher@huggingface.co>"]
readme = "README.md"
[tool.poetry.dependencies]
python = "^3.11"
docker = "^7.1.0"
loguru = "^0.7.2"
psutil = "^6.0.0"
gputil = "^1.4.0"
pandas = "^2.2.3"
pyarrow = "^... | text-generation-inference/load_tests/pyproject.toml/0 | {
"file_path": "text-generation-inference/load_tests/pyproject.toml",
"repo_id": "text-generation-inference",
"token_count": 195
} |
use crate::infer::Infer;
use crate::{
default_parameters,
server::{generate_internal, ComputeType},
Deserialize, ErrorResponse, GenerateParameters, GenerateRequest, Serialize, ToSchema,
};
use axum::extract::{Extension, Path};
use axum::http::{HeaderMap, StatusCode};
use axum::response::IntoResponse;
use ax... | text-generation-inference/router/src/kserve.rs/0 | {
"file_path": "text-generation-inference/router/src/kserve.rs",
"repo_id": "text-generation-inference",
"token_count": 3533
} |
flash_att_v2_commit_cuda := v2.6.1
flash_att_v2_commit_rocm := 47bd46e0204a95762ae48712fd1a3978827c77fd
build-flash-attention-v2-cuda:
pip install -U packaging wheel
pip install flash-attn==$(flash_att_v2_commit_cuda)
install-flash-attention-v2-cuda: build-flash-attention-v2-cuda
echo "Flash v2 installed"
build-f... | text-generation-inference/server/Makefile-flash-att-v2/0 | {
"file_path": "text-generation-inference/server/Makefile-flash-att-v2",
"repo_id": "text-generation-inference",
"token_count": 397
} |
// Adapted from turboderp exllama: https://github.com/turboderp/exllama
#ifndef _q4_matmul_cuh
#define _q4_matmul_cuh
#include <cuda_runtime.h>
#include <cuda_fp16.h>
#include <cstdint>
#include <cstdio>
#include <ATen/cuda/CUDAContext.h>
#include "q4_matrix.cuh"
#include "../tuning.h"
void q4_matmul_cuda
(
ExL... | text-generation-inference/server/exllama_kernels/exllama_kernels/cuda_func/q4_matmul.cuh/0 | {
"file_path": "text-generation-inference/server/exllama_kernels/exllama_kernels/cuda_func/q4_matmul.cuh",
"repo_id": "text-generation-inference",
"token_count": 322
} |
#include "compat.cuh"
__forceinline__ __device__ half2 dot22_8(half2(&dq)[4], const half* a_ptr, const half2 g_result)
{
half2 result = {};
const half2* a2_ptr = (const half2*)a_ptr;
#pragma unroll
for (int i = 0; i < 4; i++) result = __hfma2(dq[i], *a2_ptr++, result);
return __hadd2(result, g_resu... | text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/q_gemm_kernel_gptq.cuh/0 | {
"file_path": "text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/q_gemm_kernel_gptq.cuh",
"repo_id": "text-generation-inference",
"token_count": 4839
} |
import os
from typing import Optional
import torch
from text_generation_server.layers.attention.kv_cache import KVCache, KVScales
from text_generation_server.utils.import_utils import SYSTEM
from text_generation_server.layers.attention import Seqlen
from text_generation_server.utils.log import log_master
from text_gene... | text-generation-inference/server/text_generation_server/layers/attention/rocm.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/layers/attention/rocm.py",
"repo_id": "text-generation-inference",
"token_count": 5501
} |
import os
from dataclasses import dataclass
from typing import List, Optional, Union
import torch
from loguru import logger
from text_generation_server.utils.import_utils import SYSTEM
from text_generation_server.utils.log import log_once
from text_generation_server.utils.weights import Weight, Weights, WeightsLoader
... | text-generation-inference/server/text_generation_server/layers/gptq/__init__.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/layers/gptq/__init__.py",
"repo_id": "text-generation-inference",
"token_count": 8349
} |
import torch
from torch import nn
from typing import Tuple, Optional
from text_generation_server.utils.speculate import get_speculate
from text_generation_server.layers.linear import FastLinear
from text_generation_server.layers.tensor_parallel import (
TensorParallelHead,
TensorParallelColumnLinear,
)
class ... | text-generation-inference/server/text_generation_server/layers/medusa.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/layers/medusa.py",
"repo_id": "text-generation-inference",
"token_count": 2975
} |
# coding=utf-8
# Copyright 2024 Cohere team. All rights reserved.
#
# This code is based on EleutherAI's GPT-NeoX library and the GPT-NeoX
# and OPT implementations in this library. It has been modified from its
# original forms to accommodate minor architectural differences compared
# to GPT-NeoX and OPT used by the M... | text-generation-inference/server/text_generation_server/models/custom_modeling/flash_cohere_modeling.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/models/custom_modeling/flash_cohere_modeling.py",
"repo_id": "text-generation-inference",
"token_count": 8924
} |
from typing import List, Optional, Tuple
import torch
import torch.distributed
from torch import nn
from transformers.configuration_utils import PretrainedConfig
from transformers.modeling_utils import PreTrainedModel
from text_generation_server.layers import (
SpeculativeHead,
TensorParallelColumnLinear,
... | 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": 11278
} |
# coding=utf-8
# Copyright 2022 The Fairseq Authors and The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/... | text-generation-inference/server/text_generation_server/models/custom_modeling/opt_modeling.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/models/custom_modeling/opt_modeling.py",
"repo_id": "text-generation-inference",
"token_count": 15911
} |
import math
from typing import List, Optional
import torch
from opentelemetry import trace
from transformers import AutoTokenizer, AutoModelForCausalLM
import transformers.modeling_utils
from text_generation_server.models.flash_causal_lm import FlashCausalLM
from text_generation_server.utils import initialize_torch_d... | text-generation-inference/server/text_generation_server/models/transformers_flash_causal_lm.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/models/transformers_flash_causal_lm.py",
"repo_id": "text-generation-inference",
"token_count": 4705
} |
# coding=utf-8
# From: https://github.com/huggingface/peft/pull/1364
# Copyright 2024-present the HuggingFace Inc. team.
# Modifications by Predibase, 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 th... | text-generation-inference/server/text_generation_server/utils/merges/utils.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/utils/merges/utils.py",
"repo_id": "text-generation-inference",
"token_count": 1422
} |
## How to release
# Before the release
Simple checklist on how to make releases for `tokenizers`.
- Freeze `master` branch.
- Run all tests (Check CI has properly run)
- If any significant work, check benchmarks:
- `cd tokenizers && cargo bench` (needs to be run on latest release tag to measure difference if it's ... | tokenizers/RELEASE.md/0 | {
"file_path": "tokenizers/RELEASE.md",
"repo_id": "tokenizers",
"token_count": 1519
} |
/* eslint-disable */
var globRequire = require
console.log = (..._args: any[]) => {}
describe('quicktourExample', () => {
function require(mod: string) {
if (mod.startsWith('tokenizers')) {
return globRequire('../../')
} else {
return globRequire(mod)
}
}
it.skip('trains the tokenizer',... | tokenizers/bindings/node/examples/documentation/quicktour.test.ts/0 | {
"file_path": "tokenizers/bindings/node/examples/documentation/quicktour.test.ts",
"repo_id": "tokenizers",
"token_count": 2324
} |
{
"name": "tokenizers-linux-x64-gnu",
"version": "0.13.4-rc1",
"os": [
"linux"
],
"cpu": [
"x64"
],
"main": "tokenizers.linux-x64-gnu.node",
"files": [
"tokenizers.linux-x64-gnu.node"
],
"description": "Tokenizers platform specific bindings",
"keywords": [
"napi-rs",
"NAPI",
... | tokenizers/bindings/node/npm/linux-x64-gnu/package.json/0 | {
"file_path": "tokenizers/bindings/node/npm/linux-x64-gnu/package.json",
"repo_id": "tokenizers",
"token_count": 289
} |
use crate::arc_rwlock_serde;
use napi::bindgen_prelude::*;
use napi_derive::napi;
use serde::{Deserialize, Serialize};
use std::sync::{Arc, RwLock};
use tk::normalizers::NormalizerWrapper;
use tk::NormalizedString;
use tokenizers as tk;
/// Normalizer
#[derive(Debug, Clone, Serialize, Deserialize)]
#[napi]
pub struct ... | tokenizers/bindings/node/src/normalizers.rs/0 | {
"file_path": "tokenizers/bindings/node/src/normalizers.rs",
"repo_id": "tokenizers",
"token_count": 1886
} |
from typing import Dict, List, Optional, Tuple, Union
from tokenizers import AddedToken, EncodeInput, Encoding, InputSequence, Tokenizer
from tokenizers.decoders import Decoder
from tokenizers.models import Model
from tokenizers.normalizers import Normalizer
from tokenizers.pre_tokenizers import PreTokenizer
from toke... | tokenizers/bindings/python/py_src/tokenizers/implementations/base_tokenizer.py/0 | {
"file_path": "tokenizers/bindings/python/py_src/tokenizers/implementations/base_tokenizer.py",
"repo_id": "tokenizers",
"token_count": 6036
} |
import itertools
import os
import re
from string import Template
from typing import Any, Callable, Dict, List, NamedTuple, Optional, Tuple
from tokenizers import Encoding, Tokenizer
dirname = os.path.dirname(__file__)
css_filename = os.path.join(dirname, "visualizer-styles.css")
with open(css_filename) as f:
css... | tokenizers/bindings/python/py_src/tokenizers/tools/visualizer.py/0 | {
"file_path": "tokenizers/bindings/python/py_src/tokenizers/tools/visualizer.py",
"repo_id": "tokenizers",
"token_count": 6751
} |
use std::convert::TryInto;
use std::sync::Arc;
use std::sync::RwLock;
use crate::encoding::PyEncoding;
use crate::error::ToPyResult;
use pyo3::exceptions;
use pyo3::exceptions::PyException;
use pyo3::prelude::*;
use pyo3::types::*;
use serde::ser::SerializeStruct;
use serde::Deserializer;
use serde::Serializer;
use se... | tokenizers/bindings/python/src/processors.rs/0 | {
"file_path": "tokenizers/bindings/python/src/processors.rs",
"repo_id": "tokenizers",
"token_count": 14543
} |
import pickle
import pytest
from tokenizers.models import BPE, Model, WordLevel, WordPiece
from ..utils import bert_files, data_dir, roberta_files
class TestBPE:
def test_instantiate(self, roberta_files):
assert isinstance(BPE(), Model)
assert isinstance(BPE(), BPE)
vocab = {"a": 0, "b"... | tokenizers/bindings/python/tests/bindings/test_models.py/0 | {
"file_path": "tokenizers/bindings/python/tests/bindings/test_models.py",
"repo_id": "tokenizers",
"token_count": 2304
} |
# Visualizer
<tokenizerslangcontent>
<python>
## Annotation
[[autodoc]] tokenizers.tools.Annotation
## EncodingVisualizer
[[autodoc]] tokenizers.tools.EncodingVisualizer
- __call__
</python>
<rust>
The Rust API Reference is available directly on the [Docs.rs](https://docs.rs/tokenizers/latest/tokenizers/) webs... | tokenizers/docs/source-doc-builder/api/visualizer.mdx/0 | {
"file_path": "tokenizers/docs/source-doc-builder/api/visualizer.mdx",
"repo_id": "tokenizers",
"token_count": 134
} |
# Changelog
All notable changes to this project will be documented in this file.
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
## [0.13.2]
- Python only changes
## [0.13.1]
- [#1072] Fixing ... | tokenizers/tokenizers/CHANGELOG.md/0 | {
"file_path": "tokenizers/tokenizers/CHANGELOG.md",
"repo_id": "tokenizers",
"token_count": 3387
} |
<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
} |
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
} |
use crate::tokenizer::{NormalizedString, Normalizer, Result};
use serde::{Deserialize, Serialize};
#[derive(Clone, Debug, Deserialize, Serialize)]
#[serde(tag = "type")]
pub struct Prepend {
pub prepend: String,
}
impl Prepend {
pub fn new(prepend: String) -> Self {
Self { prepend }
}
}
impl Norm... | tokenizers/tokenizers/src/normalizers/prepend.rs/0 | {
"file_path": "tokenizers/tokenizers/src/normalizers/prepend.rs",
"repo_id": "tokenizers",
"token_count": 856
} |
// Generated by modified Perl script at https://github.com/google/sentencepiece/blob/master/data/gen_unicode_scripts_code.pl
// Unicode scripts : https://gist.github.com/Narsil/07556f26dc84a6baeff4d499e68d3cd2
// Rust adaptation : https://gist.github.com/Narsil/1df9fbbf5296a8d4d62de55dcb2fe700
#[derive(PartialEq, Debu... | tokenizers/tokenizers/src/pre_tokenizers/unicode_scripts/scripts.rs/0 | {
"file_path": "tokenizers/tokenizers/src/pre_tokenizers/unicode_scripts/scripts.rs",
"repo_id": "tokenizers",
"token_count": 46440
} |
use crate::Result;
use hf_hub::{api::sync::ApiBuilder, Repo, RepoType};
use std::collections::HashMap;
use std::path::PathBuf;
/// Defines the additional parameters available for the `from_pretrained` function
#[derive(Debug, Clone)]
pub struct FromPretrainedParameters {
pub revision: String,
pub user_agent: H... | tokenizers/tokenizers/src/utils/from_pretrained.rs/0 | {
"file_path": "tokenizers/tokenizers/src/utils/from_pretrained.rs",
"repo_id": "tokenizers",
"token_count": 906
} |
#[cfg(not(debug_assertions))]
use assert_approx_eq::assert_approx_eq;
use std::collections::HashMap;
use std::fs::read_to_string;
use std::path::Path;
#[cfg(not(debug_assertions))]
use tokenizers::models::unigram::Lattice;
use tokenizers::models::unigram::Unigram;
use tokenizers::models::unigram::UnigramTrainer;
use to... | tokenizers/tokenizers/tests/unigram.rs/0 | {
"file_path": "tokenizers/tokenizers/tests/unigram.rs",
"repo_id": "tokenizers",
"token_count": 1697
} |
# Running models on WebGPU
WebGPU is a new web standard for accelerated graphics and compute. The [API](https://developer.mozilla.org/en-US/docs/Web/API/WebGPU_API) enables web developers to use the underlying system's GPU to carry out high-performance computations directly in the browser. WebGPU is the successor to [... | transformers.js/docs/source/guides/webgpu.md/0 | {
"file_path": "transformers.js/docs/source/guides/webgpu.md",
"repo_id": "transformers.js",
"token_count": 1452
} |
function formatBytes(bytes, decimals = 0) {
const sizes = ["Bytes", "KB", "MB", "GB", "TB"];
if (bytes === 0) return "0 Bytes";
const i = parseInt(Math.floor(Math.log(bytes) / Math.log(1000)), 10);
const rounded = (bytes / Math.pow(1000, i)).toFixed(decimals);
return rounded + " " + sizes[i];
}
exp... | transformers.js/examples/code-completion/src/components/Progress.jsx/0 | {
"file_path": "transformers.js/examples/code-completion/src/components/Progress.jsx",
"repo_id": "transformers.js",
"token_count": 278
} |
import { env, AutoTokenizer, AutoModelForSequenceClassification } from '@xenova/transformers';
// Skip local model check since we are downloading the model from the Hugging Face Hub.
env.allowLocalModels = false;
class CrossEncoderSingleton {
static model_id = 'mixedbread-ai/mxbai-rerank-xsmall-v1';
static mo... | transformers.js/examples/cross-encoder/src/worker.js/0 | {
"file_path": "transformers.js/examples/cross-encoder/src/worker.js",
"repo_id": "transformers.js",
"token_count": 786
} |
// Adapted from https://www.npmjs.com/package/audiobuffer-to-wav
export function encodeWAV(samples, sampleRate = 16000) {
let offset = 44;
const buffer = new ArrayBuffer(offset + samples.length * 4);
const view = new DataView(buffer);
/* RIFF identifier */
writeString(view, 0, 'RIFF')
/* RIFF ... | transformers.js/examples/musicgen-web/src/utils.js/0 | {
"file_path": "transformers.js/examples/musicgen-web/src/utils.js",
"repo_id": "transformers.js",
"token_count": 787
} |
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