text stringlengths 5 409k | id stringlengths 14 178 | metadata dict | __index_level_0__ int64 0 572 |
|---|---|---|---|
# 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... | diffusers/tests/single_file/test_model_controlnet_single_file.py/0 | {
"file_path": "diffusers/tests/single_file/test_model_controlnet_single_file.py",
"repo_id": "diffusers",
"token_count": 1017
} | 154 |
import gc
import unittest
import torch
from diffusers import (
StableDiffusionXLPipeline,
)
from diffusers.utils.testing_utils import (
backend_empty_cache,
enable_full_determinism,
require_torch_accelerator,
slow,
torch_device,
)
from .single_file_testing_utils import SDXLSingleFileTesterMix... | diffusers/tests/single_file/test_stable_diffusion_xl_single_file.py/0 | {
"file_path": "diffusers/tests/single_file/test_stable_diffusion_xl_single_file.py",
"repo_id": "diffusers",
"token_count": 738
} | 155 |
# coding=utf-8
# 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 requir... | diffusers/utils/notify_slack_about_release.py/0 | {
"file_path": "diffusers/utils/notify_slack_about_release.py",
"repo_id": "diffusers",
"token_count": 985
} | 156 |
exclude: ^(tests/data)
default_language_version:
python: python3.10
repos:
- repo: https://github.com/pre-commit/pre-commit-hooks
rev: v5.0.0
hooks:
- id: check-added-large-files
- id: debug-statements
- id: check-merge-conflict
- id: check-case-conflict
- id: check-yaml
... | lerobot/.pre-commit-config.yaml/0 | {
"file_path": "lerobot/.pre-commit-config.yaml",
"repo_id": "lerobot",
"token_count": 412
} | 157 |
"""This scripts demonstrates how to train Diffusion Policy on the PushT environment.
Once you have trained a model with this script, you can try to evaluate it on
examples/2_evaluate_pretrained_policy.py
"""
from pathlib import Path
import torch
from lerobot.common.datasets.lerobot_dataset import LeRobotDataset, Le... | lerobot/examples/3_train_policy.py/0 | {
"file_path": "lerobot/examples/3_train_policy.py",
"repo_id": "lerobot",
"token_count": 1650
} | 158 |
#!/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/online_buffer.py/0 | {
"file_path": "lerobot/lerobot/common/datasets/online_buffer.py",
"repo_id": "lerobot",
"token_count": 7377
} | 159 |
#!/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/cam_png_format.py/0 | {
"file_path": "lerobot/lerobot/common/datasets/push_dataset_to_hub/cam_png_format.py",
"repo_id": "lerobot",
"token_count": 1314
} | 160 |
#!/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/envs/utils.py/0 | {
"file_path": "lerobot/lerobot/common/envs/utils.py",
"repo_id": "lerobot",
"token_count": 1346
} | 161 |
"""
Convert pi0 parameters from Jax to Pytorch
Follow [README of openpi](https://github.com/Physical-Intelligence/openpi) to create a new environment
and install the required librairies.
```bash
cd ~/code/openpi
source .venv/bin/activate
```
Example downloading parameters:
```bash
python
>>> import openpi.shared.dow... | lerobot/lerobot/common/policies/pi0/conversion_scripts/convert_pi0_to_hf_lerobot.py/0 | {
"file_path": "lerobot/lerobot/common/policies/pi0/conversion_scripts/convert_pi0_to_hf_lerobot.py",
"repo_id": "lerobot",
"token_count": 9301
} | 162 |
########################################################################################
# Utilities
########################################################################################
import logging
import time
import traceback
from contextlib import nullcontext
from copy import copy
from functools import cache... | lerobot/lerobot/common/robot_devices/control_utils.py/0 | {
"file_path": "lerobot/lerobot/common/robot_devices/control_utils.py",
"repo_id": "lerobot",
"token_count": 4701
} | 163 |
#!/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/utils/logging_utils.py/0 | {
"file_path": "lerobot/lerobot/common/utils/logging_utils.py",
"repo_id": "lerobot",
"token_count": 2250
} | 164 |
import os
import time
from pathlib import Path
from serial.tools import list_ports # Part of pyserial library
def find_available_ports():
if os.name == "nt": # Windows
# List COM ports using pyserial
ports = [port.device for port in list_ports.comports()]
else: # Linux/macOS
# List... | lerobot/lerobot/scripts/find_motors_bus_port.py/0 | {
"file_path": "lerobot/lerobot/scripts/find_motors_bus_port.py",
"repo_id": "lerobot",
"token_count": 508
} | 165 |
version https://git-lfs.github.com/spec/v1
oid sha256:8920d5ebab36ffcba9aa74dcd91677c121f504b4d945b472352d379f9272fabf
size 3687117
| lerobot/tests/data/save_dataset_to_safetensors/lerobot/aloha_sim_insertion_human/frame_1.safetensors/0 | {
"file_path": "lerobot/tests/data/save_dataset_to_safetensors/lerobot/aloha_sim_insertion_human/frame_1.safetensors",
"repo_id": "lerobot",
"token_count": 65
} | 166 |
version https://git-lfs.github.com/spec/v1
oid sha256:9927ec508e3335f8b10cf3682e41dedb7e647f92a2063a4196f1e48749c47bc5
size 85353
| lerobot/tests/data/save_dataset_to_safetensors/lerobot/xarm_lift_medium/frame_24.safetensors/0 | {
"file_path": "lerobot/tests/data/save_dataset_to_safetensors/lerobot/xarm_lift_medium/frame_24.safetensors",
"repo_id": "lerobot",
"token_count": 65
} | 167 |
version https://git-lfs.github.com/spec/v1
oid sha256:77cd4127a45ded2f75d85ca9c17537808517614ef16fb3035cebb1b45547acbf
size 47424
| lerobot/tests/data/save_policy_to_safetensors/pusht_diffusion/grad_stats.safetensors/0 | {
"file_path": "lerobot/tests/data/save_policy_to_safetensors/pusht_diffusion/grad_stats.safetensors",
"repo_id": "lerobot",
"token_count": 62
} | 168 |
import queue
import time
from multiprocessing import queues
from unittest.mock import MagicMock, patch
import numpy as np
import pytest
from PIL import Image
from lerobot.common.datasets.image_writer import (
AsyncImageWriter,
image_array_to_image,
safe_stop_image_writer,
write_image,
)
DUMMY_IMAGE =... | lerobot/tests/test_image_writer.py/0 | {
"file_path": "lerobot/tests/test_image_writer.py",
"repo_id": "lerobot",
"token_count": 5192
} | 169 |
# 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 applicabl... | open-r1/setup.py/0 | {
"file_path": "open-r1/setup.py",
"repo_id": "open-r1",
"token_count": 2119
} | 170 |
#!/usr/bin/env python
# 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/LI... | open-r1/src/open_r1/utils/callbacks.py/0 | {
"file_path": "open-r1/src/open_r1/utils/callbacks.py",
"repo_id": "open-r1",
"token_count": 1197
} | 171 |
# docstyle-ignore
INSTALL_CONTENT = """
# PEFT installation
! pip install peft accelerate transformers
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/peft.git
"""
| peft/docs/source/_config.py/0 | {
"file_path": "peft/docs/source/_config.py",
"repo_id": "peft",
"token_count": 75
} | 172 |
<!--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/developer_guides/torch_compile.md/0 | {
"file_path": "peft/docs/source/developer_guides/torch_compile.md",
"repo_id": "peft",
"token_count": 1014
} | 173 |
<!--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/package_reference/vera.md/0 | {
"file_path": "peft/docs/source/package_reference/vera.md",
"repo_id": "peft",
"token_count": 807
} | 174 |
PEFT_TYPE="boft"
BLOCK_NUM=8
BLOCK_SIZE=0
N_BUTTERFLY_FACTOR=1
export DATASET_NAME="oftverse/control-celeba-hq"
export PROJECT_NAME="controlnet_${PEFT_TYPE}"
export RUN_NAME="${PEFT_TYPE}_${BLOCK_NUM}${BLOCK_SIZE}${N_BUTTERFLY_FACTOR}"
export CONTROLNET_PATH=""
export MODEL_NAME="stabilityai/stable-diffusion-2-1"
# e... | peft/examples/boft_controlnet/train_controlnet.sh/0 | {
"file_path": "peft/examples/boft_controlnet/train_controlnet.sh",
"repo_id": "peft",
"token_count": 557
} | 175 |
import argparse
import os
import warnings
from typing import Optional
from huggingface_hub import HfFolder, whoami
from transformers import PretrainedConfig
def import_model_class_from_model_name_or_path(pretrained_model_name_or_path: str, revision: str):
text_encoder_config = PretrainedConfig.from_pretrained(
... | peft/examples/boft_dreambooth/utils/args_loader.py/0 | {
"file_path": "peft/examples/boft_dreambooth/utils/args_loader.py",
"repo_id": "peft",
"token_count": 5745
} | 176 |
<jupyter_start><jupyter_code>from transformers import AutoModelForSeq2SeqLM
import peft
from peft import get_peft_config, get_peft_model, get_peft_model_state_dict, IA3Config, TaskType
import torch
from datasets import load_dataset
import os
os.environ["TOKENIZERS_PARALLELISM"] = "false"
from transformers import AutoT... | peft/examples/conditional_generation/peft_ia3_seq2seq.ipynb/0 | {
"file_path": "peft/examples/conditional_generation/peft_ia3_seq2seq.ipynb",
"repo_id": "peft",
"token_count": 2685
} | 177 |
<jupyter_start><jupyter_text>Fine-tuning [Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on [timdettmers/openassistant-guanaco](https://huggingface.co/datasets/timdettmers/openassistant-guanaco) Dataset using QDora (quantized Lora w/ use_dora=True) on T4 Free Colab GPU.<jupyter_code># Install the librar... | peft/examples/dora_finetuning/QDoRA_finetuning.ipynb/0 | {
"file_path": "peft/examples/dora_finetuning/QDoRA_finetuning.ipynb",
"repo_id": "peft",
"token_count": 2118
} | 178 |
<jupyter_start><jupyter_text>Initializing weights with LoftQ by replacing LoRA weights in-place This notebook shows how to apply [LoftQ](https://arxiv.org/abs/2310.08659) initialization on our QLoRA model.In short, the idea behind LoftQ is the following. When we use QLoRA, i.e. we quantize the base model with bitsandby... | peft/examples/loftq_finetuning/LoftQ_weight_replacement.ipynb/0 | {
"file_path": "peft/examples/loftq_finetuning/LoftQ_weight_replacement.ipynb",
"repo_id": "peft",
"token_count": 2207
} | 179 |
<jupyter_start><jupyter_text>Using VB-LoRA for sequence classification In this example, we fine-tune Roberta on a sequence classification task using VB-LoRA.This notebook is adapted from `examples/sequence_classification/VeRA.ipynb`. Imports<jupyter_code>import torch
from torch.optim import AdamW
from torch.utils.data... | peft/examples/sequence_classification/VBLoRA.ipynb/0 | {
"file_path": "peft/examples/sequence_classification/VBLoRA.ipynb",
"repo_id": "peft",
"token_count": 2869
} | 180 |
# Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# Adapted from https://botorch.org/api/_modules/botorch/utils/torch.html
# TODO: To be removed once (if) https://github.com/pytorch/pytorch... | peft/src/peft/tuners/_buffer_dict.py/0 | {
"file_path": "peft/src/peft/tuners/_buffer_dict.py",
"repo_id": "peft",
"token_count": 2442
} | 181 |
// Author: Yao Feng
// Date: 2023/08
// Description: cuda kernel for fast block diag
#include <ATen/ATen.h>
#include <cuda.h>
#include <cuda_runtime.h>
#include <vector>
namespace{
template <typename scalar_t>
__global__ void forward_fast_block_diag_cuda_kernel(
const scalar_t* __restrict__ input, //[z, N, b... | peft/src/peft/tuners/boft/fbd/fbd_cuda_kernel.cu/0 | {
"file_path": "peft/src/peft/tuners/boft/fbd/fbd_cuda_kernel.cu",
"repo_id": "peft",
"token_count": 1511
} | 182 |
# 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/hra/layer.py/0 | {
"file_path": "peft/src/peft/tuners/hra/layer.py",
"repo_id": "peft",
"token_count": 8755
} | 183 |
# 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/torchao.py/0 | {
"file_path": "peft/src/peft/tuners/lora/torchao.py",
"repo_id": "peft",
"token_count": 2496
} | 184 |
# 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/poly/config.py/0 | {
"file_path": "peft/src/peft/tuners/poly/config.py",
"repo_id": "peft",
"token_count": 1681
} | 185 |
# 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/vera/bnb.py/0 | {
"file_path": "peft/src/peft/tuners/vera/bnb.py",
"repo_id": "peft",
"token_count": 8510
} | 186 |
# 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/utils/other.py/0 | {
"file_path": "peft/src/peft/utils/other.py",
"repo_id": "peft",
"token_count": 12804
} | 187 |
# 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_feature_extraction_models.py/0 | {
"file_path": "peft/tests/test_feature_extraction_models.py",
"repo_id": "peft",
"token_count": 3985
} | 188 |
# 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_stablediffusion.py/0 | {
"file_path": "peft/tests/test_stablediffusion.py",
"repo_id": "peft",
"token_count": 6040
} | 189 |
*This guideline is very much a work-in-progress.*
Contributions to `timm` for code, documentation, tests are more than welcome!
There haven't been any formal guidelines to date so please bear with me, and feel free to add to this guide.
# Coding style
Code linting and auto-format (black) are not currently in place ... | pytorch-image-models/CONTRIBUTING.md/0 | {
"file_path": "pytorch-image-models/CONTRIBUTING.md",
"repo_id": "pytorch-image-models",
"token_count": 1223
} | 190 |
# Sharing and Loading Models From the Hugging Face Hub
The `timm` library has a built-in integration with the Hugging Face Hub, making it easy to share and load models from the 🤗 Hub.
In this short guide, we'll see how to:
1. Share a `timm` model on the Hub
2. How to load that model back from the Hub
## Authent... | pytorch-image-models/hfdocs/source/hf_hub.mdx/0 | {
"file_path": "pytorch-image-models/hfdocs/source/hf_hub.mdx",
"repo_id": "pytorch-image-models",
"token_count": 593
} | 191 |
# TResNet
A **TResNet** is a variant on a [ResNet](https://paperswithcode.com/method/resnet) that aim to boost accuracy while maintaining GPU training and inference efficiency. They contain several design tricks including a SpaceToDepth stem, [Anti-Alias downsampling](https://paperswithcode.com/method/anti-alias-down... | pytorch-image-models/hfdocs/source/models/tresnet.mdx/0 | {
"file_path": "pytorch-image-models/hfdocs/source/models/tresnet.mdx",
"repo_id": "pytorch-image-models",
"token_count": 4202
} | 192 |
import numpy as np
import pandas as pd
results = {
'results-imagenet.csv': [
'results-imagenet-real.csv',
'results-imagenetv2-matched-frequency.csv',
'results-sketch.csv'
],
'results-imagenet-a-clean.csv': [
'results-imagenet-a.csv',
],
'results-imagenet-r-clean.csv... | pytorch-image-models/results/generate_csv_results.py/0 | {
"file_path": "pytorch-image-models/results/generate_csv_results.py",
"repo_id": "pytorch-image-models",
"token_count": 1453
} | 193 |
from .version import __version__ as __version__
from .layers import (
is_scriptable as is_scriptable,
is_exportable as is_exportable,
set_scriptable as set_scriptable,
set_exportable as set_exportable,
)
from .models import (
create_model as create_model,
list_models as list_models,
list_pre... | pytorch-image-models/timm/__init__.py/0 | {
"file_path": "pytorch-image-models/timm/__init__.py",
"repo_id": "pytorch-image-models",
"token_count": 219
} | 194 |
""" Mixup and Cutmix
Papers:
mixup: Beyond Empirical Risk Minimization (https://arxiv.org/abs/1710.09412)
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features (https://arxiv.org/abs/1905.04899)
Code Reference:
CutMix: https://github.com/clovaai/CutMix-PyTorch
Hacked together by / Co... | pytorch-image-models/timm/data/mixup.py/0 | {
"file_path": "pytorch-image-models/timm/data/mixup.py",
"repo_id": "pytorch-image-models",
"token_count": 7225
} | 195 |
""" Tensorflow Preprocessing Adapter
Allows use of Tensorflow preprocessing pipeline in PyTorch Transform
Copyright of original Tensorflow code below.
Hacked together by / Copyright 2020 Ross Wightman
"""
# Copyright 2018 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.... | pytorch-image-models/timm/data/tf_preprocessing.py/0 | {
"file_path": "pytorch-image-models/timm/data/tf_preprocessing.py",
"repo_id": "pytorch-image-models",
"token_count": 3775
} | 196 |
""" Conv2d w/ Same Padding
Hacked together by / Copyright 2020 Ross Wightman
"""
import torch
import torch.nn as nn
import torch.nn.functional as F
from typing import Tuple, Optional
from .config import is_exportable, is_scriptable
from .padding import pad_same, pad_same_arg, get_padding_value
_USE_EXPORT_CONV = Fa... | pytorch-image-models/timm/layers/conv2d_same.py/0 | {
"file_path": "pytorch-image-models/timm/layers/conv2d_same.py",
"repo_id": "pytorch-image-models",
"token_count": 1560
} | 197 |
""" Global Response Normalization Module
Based on the GRN layer presented in
`ConvNeXt-V2 - Co-designing and Scaling ConvNets with Masked Autoencoders` - https://arxiv.org/abs/2301.00808
This implementation
* works for both NCHW and NHWC tensor layouts
* uses affine param names matching existing torch norm layers
* s... | pytorch-image-models/timm/layers/grn.py/0 | {
"file_path": "pytorch-image-models/timm/layers/grn.py",
"repo_id": "pytorch-image-models",
"token_count": 565
} | 198 |
""" Padding Helpers
Hacked together by / Copyright 2020 Ross Wightman
"""
import math
from typing import List, Tuple, Union
import torch
import torch.nn.functional as F
from .helpers import to_2tuple
# Calculate symmetric padding for a convolution
def get_padding(kernel_size: int, stride: int = 1, dilation: int = ... | pytorch-image-models/timm/layers/padding.py/0 | {
"file_path": "pytorch-image-models/timm/layers/padding.py",
"repo_id": "pytorch-image-models",
"token_count": 1439
} | 199 |
from typing import Callable, Tuple, Type, Union
import torch
LayerType = Union[str, Callable, Type[torch.nn.Module]]
PadType = Union[str, int, Tuple[int, int]]
| pytorch-image-models/timm/layers/typing.py/0 | {
"file_path": "pytorch-image-models/timm/layers/typing.py",
"repo_id": "pytorch-image-models",
"token_count": 55
} | 200 |
import collections.abc
import math
import re
from collections import defaultdict
from itertools import chain
from typing import Any, Callable, Dict, Iterator, Optional, Tuple, Type, Union
import torch
import torch.utils.checkpoint
from torch import nn as nn
from torch import Tensor
from timm.layers import use_reentra... | pytorch-image-models/timm/models/_manipulate.py/0 | {
"file_path": "pytorch-image-models/timm/models/_manipulate.py",
"repo_id": "pytorch-image-models",
"token_count": 4690
} | 201 |
""" ConvNeXt
Papers:
* `A ConvNet for the 2020s` - https://arxiv.org/pdf/2201.03545.pdf
@Article{liu2022convnet,
author = {Zhuang Liu and Hanzi Mao and Chao-Yuan Wu and Christoph Feichtenhofer and Trevor Darrell and Saining Xie},
title = {A ConvNet for the 2020s},
journal = {Proceedings of the IEEE/CVF Confer... | pytorch-image-models/timm/models/convnext.py/0 | {
"file_path": "pytorch-image-models/timm/models/convnext.py",
"repo_id": "pytorch-image-models",
"token_count": 27273
} | 202 |
# FastViT for PyTorch
#
# Original implementation and weights from https://github.com/apple/ml-fastvit
#
# For licensing see accompanying LICENSE file at https://github.com/apple/ml-fastvit/tree/main
# Original work is copyright (C) 2023 Apple Inc. All Rights Reserved.
#
import os
from functools import partial
from typ... | pytorch-image-models/timm/models/fastvit.py/0 | {
"file_path": "pytorch-image-models/timm/models/fastvit.py",
"repo_id": "pytorch-image-models",
"token_count": 29338
} | 203 |
""" Pytorch Inception-V4 implementation
Sourced from https://github.com/Cadene/tensorflow-model-zoo.torch (MIT License) which is
based upon Google's Tensorflow implementation and pretrained weights (Apache 2.0 License)
"""
from functools import partial
import torch
import torch.nn as nn
from timm.data import IMAGENET... | pytorch-image-models/timm/models/inception_v4.py/0 | {
"file_path": "pytorch-image-models/timm/models/inception_v4.py",
"repo_id": "pytorch-image-models",
"token_count": 5547
} | 204 |
""" Pyramid Vision Transformer v2
@misc{wang2021pvtv2,
title={PVTv2: Improved Baselines with Pyramid Vision Transformer},
author={Wenhai Wang and Enze Xie and Xiang Li and Deng-Ping Fan and Kaitao Song and Ding Liang and
Tong Lu and Ping Luo and Ling Shao},
year={2021},
eprint={2106.137... | pytorch-image-models/timm/models/pvt_v2.py/0 | {
"file_path": "pytorch-image-models/timm/models/pvt_v2.py",
"repo_id": "pytorch-image-models",
"token_count": 9062
} | 205 |
""" Swin Transformer V2
A PyTorch impl of : `Swin Transformer V2: Scaling Up Capacity and Resolution`
- https://arxiv.org/abs/2111.09883
Code/weights from https://github.com/microsoft/Swin-Transformer, original copyright/license info below
Modifications and additions for timm hacked together by / Copyright 2022, ... | pytorch-image-models/timm/models/swin_transformer_v2.py/0 | {
"file_path": "pytorch-image-models/timm/models/swin_transformer_v2.py",
"repo_id": "pytorch-image-models",
"token_count": 21258
} | 206 |
"""Pytorch impl of Aligned Xception 41, 65, 71
This is a correct, from scratch impl of Aligned Xception (Deeplab) models compatible with TF weights at
https://github.com/tensorflow/models/blob/master/research/deeplab/g3doc/model_zoo.md
Hacked together by / Copyright 2020 Ross Wightman
"""
from functools import partia... | pytorch-image-models/timm/models/xception_aligned.py/0 | {
"file_path": "pytorch-image-models/timm/models/xception_aligned.py",
"repo_id": "pytorch-image-models",
"token_count": 7780
} | 207 |
""" PyTorch impl of LaProp optimizer
Code simplified from https://github.com/Z-T-WANG/LaProp-Optimizer, MIT License
Paper: LaProp: Separating Momentum and Adaptivity in Adam, https://arxiv.org/abs/2002.04839
@article{ziyin2020laprop,
title={LaProp: a Better Way to Combine Momentum with Adaptive Gradient},
author... | pytorch-image-models/timm/optim/laprop.py/0 | {
"file_path": "pytorch-image-models/timm/optim/laprop.py",
"repo_id": "pytorch-image-models",
"token_count": 2264
} | 208 |
""" Cosine Scheduler
Cosine LR schedule with warmup, cycle/restarts, noise, k-decay.
Hacked together by / Copyright 2021 Ross Wightman
"""
import logging
import math
import numpy as np
import torch
from typing import List
from .scheduler import Scheduler
_logger = logging.getLogger(__name__)
class CosineLRSchedu... | pytorch-image-models/timm/scheduler/cosine_lr.py/0 | {
"file_path": "pytorch-image-models/timm/scheduler/cosine_lr.py",
"repo_id": "pytorch-image-models",
"token_count": 2070
} | 209 |
""" JIT scripting/tracing utils
Hacked together by / Copyright 2020 Ross Wightman
"""
import os
import torch
def set_jit_legacy():
""" Set JIT executor to legacy w/ support for op fusion
This is hopefully a temporary need in 1.5/1.5.1/1.6 to restore performance due to changes
in the JIT executor. These ... | pytorch-image-models/timm/utils/jit.py/0 | {
"file_path": "pytorch-image-models/timm/utils/jit.py",
"repo_id": "pytorch-image-models",
"token_count": 1035
} | 210 |
repos:
- repo: https://github.com/astral-sh/ruff-pre-commit
rev: v0.2.1
hooks:
- id: ruff
args:
- --fix
- id: ruff-format
- repo: https://github.com/pre-commit/pre-commit-hooks
rev: v4.5.0
hooks:
- id: check-merge-conflict
- id: check-yaml
| smolagents/.pre-commit-config.yaml/0 | {
"file_path": "smolagents/.pre-commit-config.yaml",
"repo_id": "smolagents",
"token_count": 158
} | 211 |
<!--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/guided_tour.mdx/0 | {
"file_path": "smolagents/docs/source/en/guided_tour.mdx",
"repo_id": "smolagents",
"token_count": 6522
} | 212 |
<!--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/examples/text_to_sql.mdx/0 | {
"file_path": "smolagents/docs/source/hi/examples/text_to_sql.mdx",
"repo_id": "smolagents",
"token_count": 5208
} | 213 |
<!--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/guided_tour.mdx/0 | {
"file_path": "smolagents/docs/source/zh/guided_tour.mdx",
"repo_id": "smolagents",
"token_count": 9321
} | 214 |
# Open Deep Research
Welcome to this open replication of [OpenAI's Deep Research](https://openai.com/index/introducing-deep-research/)!
Read more about this implementation's goal and methods [in our blog post](https://huggingface.co/blog/open-deep-research).
This agent achieves 55% pass@1 on GAIA validation set, vs ... | smolagents/examples/open_deep_research/README.md/0 | {
"file_path": "smolagents/examples/open_deep_research/README.md",
"repo_id": "smolagents",
"token_count": 188
} | 215 |
from sqlalchemy import (
Column,
Float,
Integer,
MetaData,
String,
Table,
create_engine,
insert,
inspect,
text,
)
engine = create_engine("sqlite:///:memory:")
metadata_obj = MetaData()
# create city SQL table
table_name = "receipts"
receipts = Table(
table_name,
metada... | smolagents/examples/text_to_sql.py/0 | {
"file_path": "smolagents/examples/text_to_sql.py",
"repo_id": "smolagents",
"token_count": 858
} | 216 |
import ast
import builtins
from itertools import zip_longest
from typing import Set
from .utils import BASE_BUILTIN_MODULES, get_source
_BUILTIN_NAMES = set(vars(builtins))
class MethodChecker(ast.NodeVisitor):
"""
Checks that a method
- only uses defined names
- contains no local imports (e.g. num... | smolagents/src/smolagents/tool_validation.py/0 | {
"file_path": "smolagents/src/smolagents/tool_validation.py",
"repo_id": "smolagents",
"token_count": 4261
} | 217 |
import pytest
from smolagents.agents import ToolCall
from smolagents.memory import (
ActionStep,
AgentMemory,
ChatMessage,
MemoryStep,
Message,
MessageRole,
PlanningStep,
SystemPromptStep,
TaskStep,
)
class TestAgentMemory:
def test_initialization(self):
system_prompt ... | smolagents/tests/test_memory.py/0 | {
"file_path": "smolagents/tests/test_memory.py",
"repo_id": "smolagents",
"token_count": 2092
} | 218 |
# Fetch and extract the TGI sources
FROM alpine AS tgi
RUN mkdir -p /tgi
# Fetch the optimum-neuron sources directly to avoid relying on pypi deployments
FROM alpine AS optimum-neuron
RUN mkdir -p /optimum-neuron
ADD https://github.com/huggingface/optimum-neuron/archive/refs/tags/v0.0.28.tar.gz /optimum-neuron/sources... | text-generation-inference/Dockerfile.neuron/0 | {
"file_path": "text-generation-inference/Dockerfile.neuron",
"repo_id": "text-generation-inference",
"token_count": 2067
} | 219 |
# Text-generation-inference - Neuron backend for AWS Trainium and inferentia2
## Description
This is the TGI backend for AWS Neuron Trainium and Inferentia family of chips.
This backend is composed of:
- the AWS Neuron SDK,
- the legacy v2 TGI launcher and router,
- a neuron specific inference server for text-genera... | text-generation-inference/backends/neuron/README.md/0 | {
"file_path": "text-generation-inference/backends/neuron/README.md",
"repo_id": "text-generation-inference",
"token_count": 211
} | 220 |
from helpers import create_request
from text_generation_server.generator import NeuronGenerator
from text_generation_server.pb.generate_pb2 import Batch
def test_continuous_batching_two_requests(neuron_model_config):
"""Verify that two requests added to the batch at different generation steps
generate the sam... | text-generation-inference/backends/neuron/tests/server/test_continuous_batching.py/0 | {
"file_path": "text-generation-inference/backends/neuron/tests/server/test_continuous_batching.py",
"repo_id": "text-generation-inference",
"token_count": 1261
} | 221 |
#ifndef TGI_BACKEND_TRTLLM
#define TGI_BACKEND_TRTLLM
#include <cmath>
#include <cstdint>
#include <expected>
#include <fstream>
#include <list>
#include <span>
#include <nlohmann/json.hpp>
#include <spdlog/spdlog.h>
#include <spdlog/fmt/fmt.h>
#include <tensorrt_llm/executor/executor.h>
namespace huggingface::tgi:... | text-generation-inference/backends/trtllm/csrc/backend.hpp/0 | {
"file_path": "text-generation-inference/backends/trtllm/csrc/backend.hpp",
"repo_id": "text-generation-inference",
"token_count": 3772
} | 222 |
//! Text Generation gRPC client library
use async_trait::async_trait;
use thiserror::Error;
use tonic::transport;
use tonic::Status;
#[allow(clippy::derive_partial_eq_without_eq)]
mod pb;
mod grpc_client;
mod sharded_client;
pub use grpc_client::Client;
pub use pb::generate::v2::{
Batch, CachedBatch, FinishReas... | text-generation-inference/backends/v2/src/client/mod.rs/0 | {
"file_path": "text-generation-inference/backends/v2/src/client/mod.rs",
"repo_id": "text-generation-inference",
"token_count": 1194
} | 223 |
use crate::block_allocator::{Allocator, BlockAllocation};
use slotmap::{DefaultKey, SlotMap};
use std::hash::{Hash, Hasher};
use std::{
collections::{BTreeSet, HashMap},
sync::Arc,
};
fn hash(slice: &[u32]) -> u64 {
assert!(!slice.is_empty());
if slice.len() == 1 {
slice[0] as u64
} else {
... | text-generation-inference/backends/v3/src/radix.rs/0 | {
"file_path": "text-generation-inference/backends/v3/src/radix.rs",
"repo_id": "text-generation-inference",
"token_count": 14966
} | 224 |
import pytest
from text_generation import Client, AsyncClient
from text_generation.errors import NotFoundError, ValidationError
from text_generation.types import FinishReason
def test_generate(llama_7b_url, hf_headers):
client = Client(llama_7b_url, hf_headers)
response = client.generate("test", max_new_toke... | text-generation-inference/clients/python/tests/test_client.py/0 | {
"file_path": "text-generation-inference/clients/python/tests/test_client.py",
"repo_id": "text-generation-inference",
"token_count": 2112
} | 225 |
# Neuron backend for AWS Trainium and Inferentia
The Neuron backend allows the deployment of TGI on AWS Trainium and Inferentia family of chips.
The following hardware targets are supported:
- Trainium 1,
- Inferentia 2.
## Features
The basic TGI features are supported:
- continuous batching,
- token streaming,
- ... | text-generation-inference/docs/source/backends/neuron.md/0 | {
"file_path": "text-generation-inference/docs/source/backends/neuron.md",
"repo_id": "text-generation-inference",
"token_count": 2226
} | 226 |
# LoRA (Low-Rank Adaptation)
## What is LoRA?
LoRA is a technique that allows for efficent fine-tuning a model while only updating a small portion of the model's weights. This is useful when you have a large model that has been pre-trained on a large dataset, but you want to fine-tune it on a smaller dataset or for a... | text-generation-inference/docs/source/conceptual/lora.md/0 | {
"file_path": "text-generation-inference/docs/source/conceptual/lora.md",
"repo_id": "text-generation-inference",
"token_count": 1339
} | 227 |
# Quick Tour
The easiest way of getting started is using the official Docker container. Install Docker following [their installation instructions](https://docs.docker.com/get-docker/).
## Launching TGI
Let's say you want to deploy [teknium/OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mist... | text-generation-inference/docs/source/quicktour.md/0 | {
"file_path": "text-generation-inference/docs/source/quicktour.md",
"repo_id": "text-generation-inference",
"token_count": 1206
} | 228 |
[
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [
{
"id": 17934,
"logprob": null,
"text": "Pour"
},
{
"id": 49833,
"logprob": -10.5625,
"text": " dé... | text-generation-inference/integration-tests/models/__snapshots__/test_bloom_560m/test_bloom_560m_load.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_bloom_560m/test_bloom_560m_load.json",
"repo_id": "text-generation-inference",
"token_count": 7244
} | 229 |
[
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [],
"seed": null,
"tokens": [
{
"id": 185,
"logprob": -1.546875,
"special": false,
"text": "\n"
},
{
... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_deepseek_v2/test_flash_deepseek_v2_load.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_deepseek_v2/test_flash_deepseek_v2_load.json",
"repo_id": "text-generation-inference",
"token_count": 4036
} | 230 |
[
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [],
"seed": null,
"tokens": [
{
"id": 29896,
"logprob": -0.7709961,
"special": false,
"text": "1"
},
{
... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_grammar_llama/test_flash_llama_grammar_load.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_grammar_llama/test_flash_llama_grammar_load.json",
"repo_id": "text-generation-inference",
"token_count": 4039
} | 231 |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [],
"seed": 0,
"tokens": [
{
"id": 13,
"logprob": -2.2539062,
"special": false,
"text": "."
},
{
"id": 578,
"logprob": -0.15... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_llama_gptq/test_flash_llama_gptq_all_params.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_llama_gptq/test_flash_llama_gptq_all_params.json",
"repo_id": "text-generation-inference",
"token_count": 859
} | 232 |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [],
"seed": null,
"tokens": [
{
"id": 20910,
"logprob": -0.96484375,
"special": false,
"text": "Grad"
},
{
"id": 722,
"logpr... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_mixtral/test_flash_mixtral.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_mixtral/test_flash_mixtral.json",
"repo_id": "text-generation-inference",
"token_count": 868
} | 233 |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [],
"seed": null,
"tokens": [
{
"id": 25,
"logprob": -2.3203125,
"special": false,
"text": ":"
},
{
"id": 1391,
"logprob": -... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_phi/test_flash_phi.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_phi/test_flash_phi.json",
"repo_id": "text-generation-inference",
"token_count": 880
} | 234 |
{
"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
} | 235 |
{
"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
} | 236 |
import pytest
@pytest.fixture(scope="module")
def bloom_560_handle(launcher):
with launcher("bigscience/bloom-560m", num_shard=1) as handle:
yield handle
@pytest.fixture(scope="module")
async def bloom_560(bloom_560_handle):
await bloom_560_handle.health(240)
return bloom_560_handle.client
@py... | text-generation-inference/integration-tests/models/test_bloom_560m.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_bloom_560m.py",
"repo_id": "text-generation-inference",
"token_count": 783
} | 237 |
import pytest
@pytest.fixture(scope="module")
def flash_gemma_gptq_handle(launcher):
with launcher("TechxGenus/gemma-2b-GPTQ", num_shard=1, quantize="gptq") as handle:
yield handle
@pytest.fixture(scope="module")
async def flash_gemma_gptq(flash_gemma_gptq_handle):
await flash_gemma_gptq_handle.heal... | text-generation-inference/integration-tests/models/test_flash_gemma_gptq.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_flash_gemma_gptq.py",
"repo_id": "text-generation-inference",
"token_count": 804
} | 238 |
import pytest
@pytest.fixture(scope="module")
def flash_mixtral_gptq_handle(launcher):
with launcher(
"TheBloke/Mixtral-8x7B-Instruct-v0.1-GPTQ",
revision="gptq-4bit-128g-actorder_True",
num_shard=2,
) as handle:
yield handle
@pytest.fixture(scope="module")
async def flash_mi... | text-generation-inference/integration-tests/models/test_flash_mixtral_gptq.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_flash_mixtral_gptq.py",
"repo_id": "text-generation-inference",
"token_count": 950
} | 239 |
import pytest
import requests
from pydantic import BaseModel
from typing import List
@pytest.fixture(scope="module")
def llama_grammar_handle(launcher):
with launcher(
"TinyLlama/TinyLlama-1.1B-Chat-v1.0",
num_shard=1,
disable_grammar_support=False,
use_flash_attention=False,
... | text-generation-inference/integration-tests/models/test_grammar_response_format_llama.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_grammar_response_format_llama.py",
"repo_id": "text-generation-inference",
"token_count": 1447
} | 240 |
import pytest
@pytest.fixture
async def tgi_service(neuron_launcher, neuron_model_config):
model_name_or_path = neuron_model_config["neuron_model_path"]
service_name = neuron_model_config["name"]
with neuron_launcher(service_name, model_name_or_path) as tgi_service:
await tgi_service.health(600)
... | text-generation-inference/integration-tests/neuron/integration/test_generate.py/0 | {
"file_path": "text-generation-inference/integration-tests/neuron/integration/test_generate.py",
"repo_id": "text-generation-inference",
"token_count": 1378
} | 241 |
import datasets
import json
dataset = datasets.load_dataset("ccdv/govreport-summarization")
max_new_tokens = 50
conversations = []
for i, item in enumerate(dataset["test"]):
report = item["report"]
messages = [{"from": "human", "value": f"Summarize this report: ```{report}```"}]
conversations.append(... | text-generation-inference/load_tests/long.py/0 | {
"file_path": "text-generation-inference/load_tests/long.py",
"repo_id": "text-generation-inference",
"token_count": 156
} | 242 |
use serde::{Deserialize, Serialize};
#[derive(Clone, Debug, Serialize, Deserialize)]
#[serde(tag = "model_type")]
#[serde(rename_all = "snake_case")]
pub struct LlavaNext {
pub(crate) text_config: TextConfig,
pub(crate) vision_config: VisionConfig,
pub(crate) image_grid_pinpoints: Vec<(usize, usize)>,
}
f... | text-generation-inference/router/src/config.rs/0 | {
"file_path": "text-generation-inference/router/src/config.rs",
"repo_id": "text-generation-inference",
"token_count": 4119
} | 243 |
# Fork that adds only the correct stream to this kernel in order
# to make cuda graphs work.
awq_commit := bd1dc2d5254345cc76ab71894651fb821275bdd4
awq:
rm -rf llm-awq
git clone https://github.com/huggingface/llm-awq
build-awq: awq
cd llm-awq/ && git fetch && git checkout $(awq_commit)
cd llm-awq/awq/kernels && p... | text-generation-inference/server/Makefile-awq/0 | {
"file_path": "text-generation-inference/server/Makefile-awq",
"repo_id": "text-generation-inference",
"token_count": 183
} | 244 |
// Adapted from turboderp exllama: https://github.com/turboderp/exllama
#ifndef _cuda_buffers_cuh
#define _cuda_buffers_cuh
#include <cuda_runtime.h>
#include <cuda_fp16.h>
#include <cstdint>
#include <cstdio>
const int CUDA_MAX_DEVICES = 16;
// #ifndef _cuda_buffers_cu
// extern __constant__ half2 q4_table[16][256... | text-generation-inference/server/exllama_kernels/exllama_kernels/cuda_buffers.cuh/0 | {
"file_path": "text-generation-inference/server/exllama_kernels/exllama_kernels/cuda_buffers.cuh",
"repo_id": "text-generation-inference",
"token_count": 471
} | 245 |
#ifndef _matrix_view_cuh
#define _matrix_view_cuh
#include <cuda_runtime.h>
#include <cuda_fp16.h>
#include "quant/qdq_util.cuh"
class MatrixView_half
{
public:
const half* data;
const int height;
const int width;
__device__ __forceinline__ MatrixView_half(const half* data, const int height, const i... | text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/matrix_view.cuh/0 | {
"file_path": "text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/matrix_view.cuh",
"repo_id": "text-generation-inference",
"token_count": 1862
} | 246 |
from setuptools import setup
from torch.utils.cpp_extension import BuildExtension, CUDAExtension
import torch
extra_cuda_cflags = ["-lineinfo", "-O3"]
extra_cflags = []
if torch.version.hip:
extra_cflags = ["-DLEGACY_HIPBLAS_DIRECT=ON"]
extra_cuda_cflags += ["-DHIPBLAS_USE_HIP_HALF", "-DLEGACY_HIPBLAS_DIRECT=O... | text-generation-inference/server/exllamav2_kernels/setup.py/0 | {
"file_path": "text-generation-inference/server/exllamav2_kernels/setup.py",
"repo_id": "text-generation-inference",
"token_count": 424
} | 247 |
import os
import tempfile
import pytest
import huggingface_hub.constants
import text_generation_server.utils.hub
from text_generation_server.utils.hub import (
weight_hub_files,
download_weights,
weight_files,
EntryNotFoundError,
LocalEntryNotFoundError,
RevisionNotFoundError,
)
@pytest.fix... | text-generation-inference/server/tests/utils/test_hub.py/0 | {
"file_path": "text-generation-inference/server/tests/utils/test_hub.py",
"repo_id": "text-generation-inference",
"token_count": 1250
} | 248 |
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.utils.kernels import load_kernel
from text_generation_server.models.globals import (
ATTENTION,
BLOCK_SIZE,
)
from text_generation_... | text-generation-inference/server/text_generation_server/layers/attention/cuda.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/layers/attention/cuda.py",
"repo_id": "text-generation-inference",
"token_count": 5994
} | 249 |
from typing import List, Union
import torch
from compressed_tensors.quantization import QuantizationArgs, QuantizationType
from text_generation_server.layers.marlin.marlin import GPTQMarlin24Weight
from text_generation_server.utils.weights import Weights, WeightsLoader
class WNA16Int24Loader(WeightsLoader):
""... | text-generation-inference/server/text_generation_server/layers/compressed_tensors/wna16_int_24.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/layers/compressed_tensors/wna16_int_24.py",
"repo_id": "text-generation-inference",
"token_count": 1629
} | 250 |
from text_generation_server.layers.marlin.fp8 import GPTQMarlinFP8Linear
from text_generation_server.layers.marlin.gptq import (
GPTQMarlinWeightsLoader,
can_use_gptq_marlin,
repack_gptq_for_marlin,
)
from text_generation_server.layers.marlin.marlin import MarlinWeightsLoader
__all__ = [
"GPTQMarlinFP8... | text-generation-inference/server/text_generation_server/layers/marlin/__init__.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/layers/marlin/__init__.py",
"repo_id": "text-generation-inference",
"token_count": 195
} | 251 |
import torch
import torch.distributed
from typing import Optional, Type
from transformers import (
PreTrainedTokenizerBase,
)
from text_generation_server.models import CausalLM
from text_generation_server.models.causal_lm import CausalLMBatch
from text_generation_server.pb import generate_pb2
class BloomCausal... | text-generation-inference/server/text_generation_server/models/bloom.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/models/bloom.py",
"repo_id": "text-generation-inference",
"token_count": 543
} | 252 |
# coding=utf-8
# Copyright 2022 EleutherAI and the HuggingFace Inc. 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 G... | text-generation-inference/server/text_generation_server/models/custom_modeling/flash_neox_modeling.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/models/custom_modeling/flash_neox_modeling.py",
"repo_id": "text-generation-inference",
"token_count": 6670
} | 253 |
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