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/pipelines/stable_cascade/test_stable_cascade_decoder.py/0 | {
"file_path": "diffusers/tests/pipelines/stable_cascade/test_stable_cascade_decoder.py",
"repo_id": "diffusers",
"token_count": 5779
} | 169 |
# 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/pipelines/stable_diffusion_2/test_stable_diffusion_flax.py/0 | {
"file_path": "diffusers/tests/pipelines/stable_diffusion_2/test_stable_diffusion_flax.py",
"repo_id": "diffusers",
"token_count": 1668
} | 170 |
# 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/pipelines/stable_diffusion_xl/test_stable_diffusion_xl_inpaint.py/0 | {
"file_path": "diffusers/tests/pipelines/stable_diffusion_xl/test_stable_diffusion_xl_inpaint.py",
"repo_id": "diffusers",
"token_count": 15073
} | 171 |
# 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/pipelines/text_to_video_synthesis/test_text_to_video.py/0 | {
"file_path": "diffusers/tests/pipelines/text_to_video_synthesis/test_text_to_video.py",
"repo_id": "diffusers",
"token_count": 3755
} | 172 |
# coding=utf-8
# Copyright 2024 The HuggingFace Team 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 clone of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable... | diffusers/tests/quantization/bnb/test_mixed_int8.py/0 | {
"file_path": "diffusers/tests/quantization/bnb/test_mixed_int8.py",
"repo_id": "diffusers",
"token_count": 13320
} | 173 |
import tempfile
import unittest
import torch
from diffusers import EDMDPMSolverMultistepScheduler
from .test_schedulers import SchedulerCommonTest
class EDMDPMSolverMultistepSchedulerTest(SchedulerCommonTest):
scheduler_classes = (EDMDPMSolverMultistepScheduler,)
forward_default_kwargs = (("num_inference_s... | diffusers/tests/schedulers/test_scheduler_edm_dpmsolver_multistep.py/0 | {
"file_path": "diffusers/tests/schedulers/test_scheduler_edm_dpmsolver_multistep.py",
"repo_id": "diffusers",
"token_count": 5458
} | 174 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class UniPCMultistepSchedulerTest(SchedulerCommonTest):
scheduler_classes = (UniPCM... | diffusers/tests/schedulers/test_scheduler_unipc.py/0 | {
"file_path": "diffusers/tests/schedulers/test_scheduler_unipc.py",
"repo_id": "diffusers",
"token_count": 7568
} | 175 |
import gc
import unittest
import torch
from diffusers import (
StableDiffusionInpaintPipeline,
)
from diffusers.utils import load_image
from diffusers.utils.testing_utils import (
backend_empty_cache,
enable_full_determinism,
require_torch_accelerator,
slow,
torch_device,
)
from .single_file_... | diffusers/tests/single_file/test_stable_diffusion_inpaint_single_file.py/0 | {
"file_path": "diffusers/tests/single_file/test_stable_diffusion_inpaint_single_file.py",
"repo_id": "diffusers",
"token_count": 2043
} | 176 |
# 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/custom_init_isort.py/0 | {
"file_path": "diffusers/utils/custom_init_isort.py",
"repo_id": "diffusers",
"token_count": 5346
} | 177 |
{
"homing_offset": [
2048,
3072,
3072,
-1024,
-1024,
2048,
-2048,
2048,
-2048
],
"drive_mode": [
1,
1,
1,
0,
0,
1,
0,
1,
0
],
"start_pos": [
2056,
... | lerobot/.cache/calibration/aloha_default/right_follower.json/0 | {
"file_path": "lerobot/.cache/calibration/aloha_default/right_follower.json",
"repo_id": "lerobot",
"token_count": 717
} | 178 |
# Configure image
ARG PYTHON_VERSION=3.10
FROM python:${PYTHON_VERSION}-slim
ARG PYTHON_VERSION
ARG DEBIAN_FRONTEND=noninteractive
# Install apt dependencies
RUN apt-get update && apt-get install -y --no-install-recommends \
build-essential cmake git git-lfs \
libglib2.0-0 libgl1-mesa-glx libegl1-mesa ffmpeg ... | lerobot/docker/lerobot-cpu/Dockerfile/0 | {
"file_path": "lerobot/docker/lerobot-cpu/Dockerfile",
"repo_id": "lerobot",
"token_count": 412
} | 179 |
#!/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/utils.py/0 | {
"file_path": "lerobot/lerobot/common/datasets/utils.py",
"repo_id": "lerobot",
"token_count": 8989
} | 180 |
#!/usr/bin/env python
# Copyright 2024 Columbia Artificial Intelligence, Robotics Lab,
# 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
#... | lerobot/lerobot/common/policies/diffusion/modeling_diffusion.py/0 | {
"file_path": "lerobot/lerobot/common/policies/diffusion/modeling_diffusion.py",
"repo_id": "lerobot",
"token_count": 14466
} | 181 |
#!/usr/bin/env python
# Copyright 2024 Seungjae Lee and Yibin Wang and Haritheja Etukuru
# and H. Jin Kim and Nur Muhammad Mahi Shafiullah and Lerrel Pinto
# 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 com... | lerobot/lerobot/common/policies/vqbet/modeling_vqbet.py/0 | {
"file_path": "lerobot/lerobot/common/policies/vqbet/modeling_vqbet.py",
"repo_id": "lerobot",
"token_count": 20293
} | 182 |
#!/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/robot_devices/robots/stretch.py/0 | {
"file_path": "lerobot/lerobot/common/robot_devices/robots/stretch.py",
"repo_id": "lerobot",
"token_count": 3353
} | 183 |
import datetime as dt
import logging
import os
from dataclasses import dataclass, field
from pathlib import Path
from typing import Type
import draccus
from huggingface_hub import hf_hub_download
from huggingface_hub.errors import HfHubHTTPError
from lerobot.common import envs
from lerobot.common.optim import Optimiz... | lerobot/lerobot/configs/train.py/0 | {
"file_path": "lerobot/lerobot/configs/train.py",
"repo_id": "lerobot",
"token_count": 3287
} | 184 |
version https://git-lfs.github.com/spec/v1
oid sha256:01cfe50c537e3aef0cd5947ec0b15b321b54ecb461baf7b4f2506897158eebc8
size 111338
| lerobot/tests/data/save_dataset_to_safetensors/lerobot/pusht/frame_80.safetensors/0 | {
"file_path": "lerobot/tests/data/save_dataset_to_safetensors/lerobot/pusht/frame_80.safetensors",
"repo_id": "lerobot",
"token_count": 65
} | 185 |
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oid sha256:9bb9b195d32e05550af0edd5df88fcc761c829ab8c4b129ba970a723f39b46ee
size 68
| lerobot/tests/data/save_policy_to_safetensors/aloha_act_1000_steps/output_dict.safetensors/0 | {
"file_path": "lerobot/tests/data/save_policy_to_safetensors/aloha_act_1000_steps/output_dict.safetensors",
"repo_id": "lerobot",
"token_count": 65
} | 186 |
version https://git-lfs.github.com/spec/v1
oid sha256:4636751d82103a268ac7cf36f1e69f6356f356b9c40561a9fe8557bb9255e2ee
size 240
| lerobot/tests/data/save_policy_to_safetensors/xarm_tdmpcuse_policy/output_dict.safetensors/0 | {
"file_path": "lerobot/tests/data/save_policy_to_safetensors/xarm_tdmpcuse_policy/output_dict.safetensors",
"repo_id": "lerobot",
"token_count": 63
} | 187 |
"""
Tests for physical cameras and their mocked versions.
If the physical camera is not connected to the computer, or not working,
the test will be skipped.
Example of running a specific test:
```bash
pytest -sx tests/test_cameras.py::test_camera
```
Example of running test on a real camera connected to the computer:... | lerobot/tests/test_cameras.py/0 | {
"file_path": "lerobot/tests/test_cameras.py",
"repo_id": "lerobot",
"token_count": 2521
} | 188 |
"""
Tests for physical robots and their mocked versions.
If the physical robots are not connected to the computer, or not working,
the test will be skipped.
Example of running a specific test:
```bash
pytest -sx tests/test_robots.py::test_robot
```
Example of running test on real robots connected to the computer:
```... | lerobot/tests/test_robots.py/0 | {
"file_path": "lerobot/tests/test_robots.py",
"repo_id": "lerobot",
"token_count": 1872
} | 189 |
compute_environment: LOCAL_MACHINE
debug: false
distributed_type: MULTI_GPU
downcast_bf16: 'no'
gpu_ids: all
machine_rank: 0
main_training_function: main
mixed_precision: bf16
num_machines: 1
num_processes: 8
rdzv_backend: static
same_network: true
tpu_env: []
tpu_use_cluster: false
tpu_use_sudo: false
use_cpu: false
| open-r1/recipes/accelerate_configs/ddp.yaml/0 | {
"file_path": "open-r1/recipes/accelerate_configs/ddp.yaml",
"repo_id": "open-r1",
"token_count": 129
} | 190 |
# coding=utf-8
# 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 requir... | open-r1/src/open_r1/configs.py/0 | {
"file_path": "open-r1/src/open_r1/configs.py",
"repo_id": "open-r1",
"token_count": 1133
} | 191 |
# Builds GPU docker image of PyTorch
# Uses multi-staged approach to reduce size
# Stage 1
# Use base conda image to reduce time
FROM continuumio/miniconda3:latest AS compile-image
# Specify py version
ENV PYTHON_VERSION=3.11
# Install apt libs - copied from https://github.com/huggingface/accelerate/blob/main/docker/ac... | peft/docker/peft-cpu/Dockerfile/0 | {
"file_path": "peft/docker/peft-cpu/Dockerfile",
"repo_id": "peft",
"token_count": 649
} | 192 |
<!--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/contributing.md/0 | {
"file_path": "peft/docs/source/developer_guides/contributing.md",
"repo_id": "peft",
"token_count": 1620
} | 193 |
<!--⚠️ Note that this file is in Markdown but contain specific syntax for our doc-builder (similar to MDX) that may not be
rendered properly in your Markdown viewer.
-->
# Configuration
[`PeftConfigMixin`] is the base configuration class for storing the adapter configuration of a [`PeftModel`], and [`PromptLearningCo... | peft/docs/source/package_reference/config.md/0 | {
"file_path": "peft/docs/source/package_reference/config.md",
"repo_id": "peft",
"token_count": 224
} | 194 |
<!--⚠️ Note that this file is in Markdown but contain specific syntax for our doc-builder (similar to MDX) that may not be
rendered properly in your Markdown viewer.
-->
# Models
[`PeftModel`] is the base model class for specifying the base Transformer model and configuration to apply a PEFT method to. The base `Peft... | peft/docs/source/package_reference/peft_model.md/0 | {
"file_path": "peft/docs/source/package_reference/peft_model.md",
"repo_id": "peft",
"token_count": 564
} | 195 |
<!--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/examples/boft_controlnet/boft_controlnet.md/0 | {
"file_path": "peft/examples/boft_controlnet/boft_controlnet.md",
"repo_id": "peft",
"token_count": 2426
} | 196 |
<jupyter_start><jupyter_text>Training PEFT models with new tokens being added to the embedding layers and tokenizerIn this example, we will learn how to train a LoRA model when adding new tokens to the tokenizer and model. This is a common usecase when doing the following:1. Instruction finetuning with new tokens beind... | peft/examples/causal_language_modeling/peft_lora_clm_with_additional_tokens.ipynb/0 | {
"file_path": "peft/examples/causal_language_modeling/peft_lora_clm_with_additional_tokens.ipynb",
"repo_id": "peft",
"token_count": 4577
} | 197 |
# 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/feature_extraction/peft_lora_embedding_semantic_search.py/0 | {
"file_path": "peft/examples/feature_extraction/peft_lora_embedding_semantic_search.py",
"repo_id": "peft",
"token_count": 8775
} | 198 |
<jupyter_start><jupyter_text>Using PEFT with timm `peft` allows us to train any model with LoRA as long as the layer type is supported. Since `Conv2D` is one of the supported layer types, it makes sense to test it on image models.In this short notebook, we will demonstrate this with an image classification task using [... | peft/examples/image_classification/image_classification_timm_peft_lora.ipynb/0 | {
"file_path": "peft/examples/image_classification/image_classification_timm_peft_lora.ipynb",
"repo_id": "peft",
"token_count": 3067
} | 199 |
import argparse
import gc
import hashlib
import itertools
import logging
import math
import os
import threading
import warnings
from contextlib import nullcontext
from pathlib import Path
import datasets
import diffusers
import numpy as np
import psutil
import torch
import torch.nn.functional as F
import torch.utils.c... | peft/examples/lora_dreambooth/train_dreambooth.py/0 | {
"file_path": "peft/examples/lora_dreambooth/train_dreambooth.py",
"repo_id": "peft",
"token_count": 20030
} | 200 |
<jupyter_start><jupyter_text>Using FourierFT for sequence classification In this example, we fine-tune Roberta (base) on a sequence classification task using FourierFT. Imports<jupyter_code># To run this notebook, please run `pip install evaluate` to install additional dependencies not covered by PEFT.
import torch
f... | peft/examples/sequence_classification/FourierFT.ipynb/0 | {
"file_path": "peft/examples/sequence_classification/FourierFT.ipynb",
"repo_id": "peft",
"token_count": 2571
} | 201 |
compute_environment: LOCAL_MACHINE
debug: false ... | peft/examples/sft/configs/fsdp_config_qlora.yaml/0 | {
"file_path": "peft/examples/sft/configs/fsdp_config_qlora.yaml",
"repo_id": "peft",
"token_count": 565
} | 202 |
# 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/mapping_func.py/0 | {
"file_path": "peft/src/peft/mapping_func.py",
"repo_id": "peft",
"token_count": 2208
} | 203 |
# 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/adaption_prompt/layer.py/0 | {
"file_path": "peft/src/peft/tuners/adaption_prompt/layer.py",
"repo_id": "peft",
"token_count": 2705
} | 204 |
# 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/cpt/model.py/0 | {
"file_path": "peft/src/peft/tuners/cpt/model.py",
"repo_id": "peft",
"token_count": 3563
} | 205 |
# 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/ln_tuning/layer.py/0 | {
"file_path": "peft/src/peft/tuners/ln_tuning/layer.py",
"repo_id": "peft",
"token_count": 1852
} | 206 |
# 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/dora.py/0 | {
"file_path": "peft/src/peft/tuners/lora/dora.py",
"repo_id": "peft",
"token_count": 3595
} | 207 |
# 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/oft/config.py/0 | {
"file_path": "peft/src/peft/tuners/oft/config.py",
"repo_id": "peft",
"token_count": 4034
} | 208 |
# 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/prompt_tuning/model.py/0 | {
"file_path": "peft/src/peft/tuners/prompt_tuning/model.py",
"repo_id": "peft",
"token_count": 1486
} | 209 |
# 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/__init__.py/0 | {
"file_path": "peft/src/peft/utils/__init__.py",
"repo_id": "peft",
"token_count": 1463
} | 210 |
# 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_boft.py/0 | {
"file_path": "peft/tests/test_boft.py",
"repo_id": "peft",
"token_count": 1325
} | 211 |
# 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_loraplus.py/0 | {
"file_path": "peft/tests/test_loraplus.py",
"repo_id": "peft",
"token_count": 1312
} | 212 |
import argparse
import hashlib
import os
import mxnet as mx
import gluoncv
import torch
from timm import create_model
parser = argparse.ArgumentParser(description='Convert from MXNet')
parser.add_argument('--model', default='all', type=str, metavar='MODEL',
help='Name of model to train (default: "... | pytorch-image-models/convert/convert_from_mxnet.py/0 | {
"file_path": "pytorch-image-models/convert/convert_from_mxnet.py",
"repo_id": "pytorch-image-models",
"token_count": 1786
} | 213 |
# HRNet
**HRNet**, or **High-Resolution Net**, is a general purpose convolutional neural network for tasks like semantic segmentation, object detection and image classification. It is able to maintain high resolution representations through the whole process. We start from a high-resolution convolution stream, gradual... | pytorch-image-models/hfdocs/source/models/hrnet.mdx/0 | {
"file_path": "pytorch-image-models/hfdocs/source/models/hrnet.mdx",
"repo_id": "pytorch-image-models",
"token_count": 5058
} | 214 |
# RegNetY
**RegNetY** is a convolutional network design space with simple, regular models with parameters: depth \\( d \\), initial width \\( w_{0} > 0 \\), and slope \\( w_{a} > 0 \\), and generates a different block width \\( u_{j} \\) for each block \\( j < d \\). The key restriction for the RegNet types of model i... | pytorch-image-models/hfdocs/source/models/regnety.mdx/0 | {
"file_path": "pytorch-image-models/hfdocs/source/models/regnety.mdx",
"repo_id": "pytorch-image-models",
"token_count": 6761
} | 215 |
# Scripts
A train, validation, inference, and checkpoint cleaning script included in the github root folder. Scripts are not currently packaged in the pip release.
The training and validation scripts evolved from early versions of the [PyTorch Imagenet Examples](https://github.com/pytorch/examples). I have added sign... | pytorch-image-models/hfdocs/source/training_script.mdx/0 | {
"file_path": "pytorch-image-models/hfdocs/source/training_script.mdx",
"repo_id": "pytorch-image-models",
"token_count": 2364
} | 216 |
DEFAULT_CROP_PCT = 0.875
DEFAULT_CROP_MODE = 'center'
IMAGENET_DEFAULT_MEAN = (0.485, 0.456, 0.406)
IMAGENET_DEFAULT_STD = (0.229, 0.224, 0.225)
IMAGENET_INCEPTION_MEAN = (0.5, 0.5, 0.5)
IMAGENET_INCEPTION_STD = (0.5, 0.5, 0.5)
IMAGENET_DPN_MEAN = (124 / 255, 117 / 255, 104 / 255)
IMAGENET_DPN_STD = tuple([1 / (.0167 *... | pytorch-image-models/timm/data/constants.py/0 | {
"file_path": "pytorch-image-models/timm/data/constants.py",
"repo_id": "pytorch-image-models",
"token_count": 236
} | 217 |
""" A dataset reader that extracts images from folders
Folders are scanned recursively to find image files. Labels are based
on the folder hierarchy, just leaf folders by default.
Hacked together by / Copyright 2020 Ross Wightman
"""
import os
from typing import Dict, List, Optional, Set, Tuple, Union
from timm.util... | pytorch-image-models/timm/data/readers/reader_image_folder.py/0 | {
"file_path": "pytorch-image-models/timm/data/readers/reader_image_folder.py",
"repo_id": "pytorch-image-models",
"token_count": 1510
} | 218 |
""" Attention Pool 2D
Implementations of 2D spatial feature pooling using multi-head attention instead of average pool.
Based on idea in CLIP by OpenAI, licensed Apache 2.0
https://github.com/openai/CLIP/blob/3b473b0e682c091a9e53623eebc1ca1657385717/clip/model.py
Hacked together by / Copyright 2021 Ross Wightman
"""... | pytorch-image-models/timm/layers/attention_pool2d.py/0 | {
"file_path": "pytorch-image-models/timm/layers/attention_pool2d.py",
"repo_id": "pytorch-image-models",
"token_count": 5737
} | 219 |
""" EvoNorm in PyTorch
Based on `Evolving Normalization-Activation Layers` - https://arxiv.org/abs/2004.02967
@inproceedings{NEURIPS2020,
author = {Liu, Hanxiao and Brock, Andy and Simonyan, Karen and Le, Quoc},
booktitle = {Advances in Neural Information Processing Systems},
editor = {H. Larochelle and M. Ranzato ... | pytorch-image-models/timm/layers/evo_norm.py/0 | {
"file_path": "pytorch-image-models/timm/layers/evo_norm.py",
"repo_id": "pytorch-image-models",
"token_count": 6684
} | 220 |
""" Median Pool
Hacked together by / Copyright 2020 Ross Wightman
"""
import torch.nn as nn
import torch.nn.functional as F
from .helpers import to_2tuple, to_4tuple
class MedianPool2d(nn.Module):
""" Median pool (usable as median filter when stride=1) module.
Args:
kernel_size: size of pooling kern... | pytorch-image-models/timm/layers/median_pool.py/0 | {
"file_path": "pytorch-image-models/timm/layers/median_pool.py",
"repo_id": "pytorch-image-models",
"token_count": 883
} | 221 |
import torch
import torch.nn as nn
class SpaceToDepth(nn.Module):
bs: torch.jit.Final[int]
def __init__(self, block_size=4):
super().__init__()
assert block_size == 4
self.bs = block_size
def forward(self, x):
N, C, H, W = x.size()
x = x.view(N, C, H // self.bs, s... | pytorch-image-models/timm/layers/space_to_depth.py/0 | {
"file_path": "pytorch-image-models/timm/layers/space_to_depth.py",
"repo_id": "pytorch-image-models",
"token_count": 568
} | 222 |
""" EfficientNet, MobileNetV3, etc Blocks
Hacked together by / Copyright 2019, Ross Wightman
"""
from typing import Callable, Dict, Optional, Type
import torch
import torch.nn as nn
from torch.nn import functional as F
from timm.layers import create_conv2d, DropPath, make_divisible, create_act_layer, create_aa, to_2... | pytorch-image-models/timm/models/_efficientnet_blocks.py/0 | {
"file_path": "pytorch-image-models/timm/models/_efficientnet_blocks.py",
"repo_id": "pytorch-image-models",
"token_count": 13538
} | 223 |
""" BEiT: BERT Pre-Training of Image Transformers (https://arxiv.org/abs/2106.08254)
Model from official source: https://github.com/microsoft/unilm/tree/master/beit
@inproceedings{beit,
title={{BEiT}: {BERT} Pre-Training of Image Transformers},
author={Hangbo Bao and Li Dong and Songhao Piao and Furu Wei},
booktitle=... | pytorch-image-models/timm/models/beit.py/0 | {
"file_path": "pytorch-image-models/timm/models/beit.py",
"repo_id": "pytorch-image-models",
"token_count": 14383
} | 224 |
""" EfficientFormer
@article{li2022efficientformer,
title={EfficientFormer: Vision Transformers at MobileNet Speed},
author={Li, Yanyu and Yuan, Geng and Wen, Yang and Hu, Eric and Evangelidis, Georgios and Tulyakov,
Sergey and Wang, Yanzhi and Ren, Jian},
journal={arXiv preprint arXiv:2206.01191},
year={20... | pytorch-image-models/timm/models/efficientformer.py/0 | {
"file_path": "pytorch-image-models/timm/models/efficientformer.py",
"repo_id": "pytorch-image-models",
"token_count": 10905
} | 225 |
""" An PyTorch implementation of Hiera
Adapted for timm from originals at https://github.com/facebookresearch/hiera
"""
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
#... | pytorch-image-models/timm/models/hiera.py/0 | {
"file_path": "pytorch-image-models/timm/models/hiera.py",
"repo_id": "pytorch-image-models",
"token_count": 18103
} | 226 |
""" Multi-Scale Vision Transformer v2
@inproceedings{li2021improved,
title={MViTv2: Improved multiscale vision transformers for classification and detection},
author={Li, Yanghao and Wu, Chao-Yuan and Fan, Haoqi and Mangalam, Karttikeya and Xiong, Bo and Malik, Jitendra and Feichtenhofer, Christoph},
booktitle={... | pytorch-image-models/timm/models/mvitv2.py/0 | {
"file_path": "pytorch-image-models/timm/models/mvitv2.py",
"repo_id": "pytorch-image-models",
"token_count": 21263
} | 227 |
"""Pre-Activation ResNet v2 with GroupNorm and Weight Standardization.
A PyTorch implementation of ResNetV2 adapted from the Google Big-Transfer (BiT) source code
at https://github.com/google-research/big_transfer to match timm interfaces. The BiT weights have
been included here as pretrained models from their origina... | pytorch-image-models/timm/models/resnetv2.py/0 | {
"file_path": "pytorch-image-models/timm/models/resnetv2.py",
"repo_id": "pytorch-image-models",
"token_count": 17289
} | 228 |
""" Hybrid Vision Transformer (ViT) in PyTorch
A PyTorch implement of the Hybrid Vision Transformers as described in:
'An Image Is Worth 16 x 16 Words: Transformers for Image Recognition at Scale'
- https://arxiv.org/abs/2010.11929
`How to train your ViT? Data, Augmentation, and Regularization in Vision Transfor... | pytorch-image-models/timm/models/vision_transformer_hybrid.py/0 | {
"file_path": "pytorch-image-models/timm/models/vision_transformer_hybrid.py",
"repo_id": "pytorch-image-models",
"token_count": 8273
} | 229 |
""" AdaHessian Optimizer
Lifted from https://github.com/davda54/ada-hessian/blob/master/ada_hessian.py
Originally licensed MIT, Copyright 2020, David Samuel
"""
import torch
class Adahessian(torch.optim.Optimizer):
"""
Implements the AdaHessian algorithm from "ADAHESSIAN: An Adaptive Second OrderOptimizer fo... | pytorch-image-models/timm/optim/adahessian.py/0 | {
"file_path": "pytorch-image-models/timm/optim/adahessian.py",
"repo_id": "pytorch-image-models",
"token_count": 3131
} | 230 |
# lots of uses of these functions directly, ala 'import timm.optim.optim_factory as optim_factory', fun :/
from ._optim_factory import create_optimizer, create_optimizer_v2, optimizer_kwargs
from ._param_groups import param_groups_layer_decay, param_groups_weight_decay, group_parameters, _layer_map, _group
import war... | 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": 130
} | 231 |
""" Adaptive Gradient Clipping
An impl of AGC, as per (https://arxiv.org/abs/2102.06171):
@article{brock2021high,
author={Andrew Brock and Soham De and Samuel L. Smith and Karen Simonyan},
title={High-Performance Large-Scale Image Recognition Without Normalization},
journal={arXiv preprint arXiv:},
year={2021... | pytorch-image-models/timm/utils/agc.py/0 | {
"file_path": "pytorch-image-models/timm/utils/agc.py",
"repo_id": "pytorch-image-models",
"token_count": 661
} | 232 |
__version__ = '1.0.15'
| pytorch-image-models/timm/version.py/0 | {
"file_path": "pytorch-image-models/timm/version.py",
"repo_id": "pytorch-image-models",
"token_count": 12
} | 233 |
- title: Get started
sections:
- local: index
title: 🤗 Agents
- local: guided_tour
title: Guided tour
- title: Tutorials
sections:
- local: tutorials/building_good_agents
title: ✨ Building good agents
- local: tutorials/inspect_runs
title: 📊 Inspect your agent runs using telemetry
- loca... | smolagents/docs/source/en/_toctree.yml/0 | {
"file_path": "smolagents/docs/source/en/_toctree.yml",
"repo_id": "smolagents",
"token_count": 418
} | 234 |
<!--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/tutorials/tools.mdx/0 | {
"file_path": "smolagents/docs/source/en/tutorials/tools.mdx",
"repo_id": "smolagents",
"token_count": 3370
} | 235 |
# docstyle-ignore
INSTALL_CONTENT = """
# Installation
! pip install smolagents
# 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/smolagents.git
"""
notebook_first_cells = [{"type": "code", "content": INST... | smolagents/docs/source/zh/_config.py/0 | {
"file_path": "smolagents/docs/source/zh/_config.py",
"repo_id": "smolagents",
"token_count": 155
} | 236 |
# This is a config for E2B sandbox template.
# You can use template ID (qywp2ctmu2q7jzprcf4j) to create a sandbox:
# Python SDK
# from e2b import Sandbox, AsyncSandbox
# sandbox = Sandbox("qywp2ctmu2q7jzprcf4j") # Sync sandbox
# sandbox = await AsyncSandbox.create("qywp2ctmu2q7jzprcf4j") # Async sandbox
# JS SDK
# im... | smolagents/e2b.toml/0 | {
"file_path": "smolagents/e2b.toml",
"repo_id": "smolagents",
"token_count": 254
} | 237 |
import json
import os
import shutil
import textwrap
from pathlib import Path
# import tqdm.asyncio
from smolagents.utils import AgentError
def serialize_agent_error(obj):
if isinstance(obj, AgentError):
return {"error_type": obj.__class__.__name__, "message": obj.message}
else:
return str(obj... | smolagents/examples/open_deep_research/scripts/run_agents.py/0 | {
"file_path": "smolagents/examples/open_deep_research/scripts/run_agents.py",
"repo_id": "smolagents",
"token_count": 1425
} | 238 |
#!/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/LI... | smolagents/src/smolagents/gradio_ui.py/0 | {
"file_path": "smolagents/src/smolagents/gradio_ui.py",
"repo_id": "smolagents",
"token_count": 5258
} | 239 |
# 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_default_tools.py/0 | {
"file_path": "smolagents/tests/test_default_tools.py",
"repo_id": "smolagents",
"token_count": 1333
} | 240 |
# coding=utf-8
# Copyright 2025-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 a... | smolagents/utils/check_tests_in_ci.py/0 | {
"file_path": "smolagents/utils/check_tests_in_ci.py",
"repo_id": "smolagents",
"token_count": 729
} | 241 |
repos:
- repo: https://github.com/pre-commit/pre-commit-hooks
rev: v4.5.0
hooks:
- id: check-yaml
- id: end-of-file-fixer
exclude: crate-hashes.json
- id: trailing-whitespace
exclude: docs/source/reference/launcher.md
- repo: https://github.com/psf/black
rev: 24.2.0
... | text-generation-inference/.pre-commit-config.yaml/0 | {
"file_path": "text-generation-inference/.pre-commit-config.yaml",
"repo_id": "text-generation-inference",
"token_count": 314
} | 242 |
# Llamacpp backend
If all your dependencies are installed at the system level, running
cargo build should be sufficient. However, if you want to experiment
with different versions of llama.cpp, some additional setup is required.
## Install llama.cpp
LLAMACPP_PREFIX=$(pwd)/llama.cpp.out
git clone https://git... | text-generation-inference/backends/llamacpp/README.md/0 | {
"file_path": "text-generation-inference/backends/llamacpp/README.md",
"repo_id": "text-generation-inference",
"token_count": 297
} | 243 |
import asyncio
from pathlib import Path
from typing import List
from grpc import aio
from grpc_reflection.v1alpha import reflection
from loguru import logger
from .generator import Generator, NeuronGenerator
from .interceptor import ExceptionInterceptor
from .pb import generate_pb2, generate_pb2_grpc
class TextGene... | text-generation-inference/backends/neuron/server/text_generation_server/server.py/0 | {
"file_path": "text-generation-inference/backends/neuron/server/text_generation_server/server.py",
"repo_id": "text-generation-inference",
"token_count": 1222
} | 244 |
# Text Generation Inference - TensorRT-LLM Backend Implementation
## Description
This folder provides the sources of the TensorRT-LLM backend implementation powered by TensorRT-LLM Executor new API
## Simplified Request Sequence
```mermaid
sequenceDiagram
actor User
participant TextGenerationInference.HttpS... | text-generation-inference/backends/trtllm/README.md/0 | {
"file_path": "text-generation-inference/backends/trtllm/README.md",
"repo_id": "text-generation-inference",
"token_count": 1019
} | 245 |
///
/// Extract the first line of the provided string reference.
/// If there is no lines in the buffer, it returns a string
/// which content is defined by the content of `fail`
/// # Arguments
///
/// * `s`: The string buffer to extract the first-line from
/// * `fail`: A string content which is returned if no lines ... | text-generation-inference/backends/trtllm/src/utils.rs/0 | {
"file_path": "text-generation-inference/backends/trtllm/src/utils.rs",
"repo_id": "text-generation-inference",
"token_count": 201
} | 246 |
use std::sync::Arc;
use tokio::sync::{mpsc, oneshot};
use crate::radix::RadixAllocator;
#[derive(Debug, Clone)]
pub struct BlockAllocation {
pub allocation_id: u64,
pub blocks: Vec<u32>,
pub slots: Vec<u32>,
/// Prefix that was cached and for which the KV does not have to
/// be recomputed.
p... | text-generation-inference/backends/v3/src/block_allocator.rs/0 | {
"file_path": "text-generation-inference/backends/v3/src/block_allocator.rs",
"repo_id": "text-generation-inference",
"token_count": 3008
} | 247 |
/// MIT License
//
// Copyright (c) 2020 hatoo
//
// Permission is hereby granted, free of charge, to any person obtaining a copy
// of this software and associated documentation files (the "Software"), to deal
// in the Software without restriction, including without limitation the rights
// to use, copy, modify, merg... | text-generation-inference/benchmark/src/utils.rs/0 | {
"file_path": "text-generation-inference/benchmark/src/utils.rs",
"repo_id": "text-generation-inference",
"token_count": 598
} | 248 |
{
"git+https://github.com/dottxt-ai/outlines-core.git?rev=ba10c619fc9bf3c487e43f49bdecb95a24bb465c#outlines-core@0.1.0": "1j9dcd831b0bmmjk2n4aag3x47qnqmkpg4gqpvwwyic7744llbfm"
} | text-generation-inference/crate-hashes.json/0 | {
"file_path": "text-generation-inference/crate-hashes.json",
"repo_id": "text-generation-inference",
"token_count": 106
} | 249 |
# Using TGI CLI
You can use TGI command-line interface (CLI) to download weights, serve and quantize models, or get information on serving parameters. To install the CLI, please refer to [the installation section](../installation#install-cli).
`text-generation-server` lets you download the model with `download-weight... | text-generation-inference/docs/source/basic_tutorials/using_cli.md/0 | {
"file_path": "text-generation-inference/docs/source/basic_tutorials/using_cli.md",
"repo_id": "text-generation-inference",
"token_count": 323
} | 250 |
# Using TGI with AMD GPUs
TGI is supported and tested on [AMD Instinct MI210](https://www.amd.com/en/products/accelerators/instinct/mi200/mi210.html), [MI250](https://www.amd.com/en/products/accelerators/instinct/mi200/mi250.html) and [MI300](https://www.amd.com/en/products/accelerators/instinct/mi300.html) GPUs. The ... | text-generation-inference/docs/source/installation_amd.md/0 | {
"file_path": "text-generation-inference/docs/source/installation_amd.md",
"repo_id": "text-generation-inference",
"token_count": 1047
} | 251 |
import copy
import logging
import sys
from tempfile import TemporaryDirectory
import huggingface_hub
import pytest
import docker
import hashlib
import os
import tempfile
from docker.errors import NotFound
TEST_ORGANIZATION = "optimum-internal-testing"
TEST_CACHE_REPO_ID = f"{TEST_ORGANIZATION}/neuron-testing-cache"... | text-generation-inference/integration-tests/fixtures/neuron/model.py/0 | {
"file_path": "text-generation-inference/integration-tests/fixtures/neuron/model.py",
"repo_id": "text-generation-inference",
"token_count": 3604
} | 252 |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [],
"seed": 0,
"tokens": [
{
"id": 5380,
"logprob": 0.0,
"special": false,
"text": "?\n"
},
{
"id": 34564,
"logprob": 0.0,
... | text-generation-inference/integration-tests/models/__snapshots__/test_compressed_tensors_w8a8_int/test_compressed_tensors_w8a8_int_all_params.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_compressed_tensors_w8a8_int/test_compressed_tensors_w8a8_int_all_params.json",
"repo_id": "text-generation-inference",
"token_count": 853
} | 253 |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [],
"seed": null,
"tokens": [
{
"id": 13,
"logprob": -1.9306641,
"special": false,
"text": "\n"
},
{
"id": 5618,
"logprob": ... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_awq/test_flash_llama_awq.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_awq/test_flash_llama_awq.json",
"repo_id": "text-generation-inference",
"token_count": 868
} | 254 |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [],
"seed": null,
"tokens": [
{
"id": 604,
"logprob": -2.4296875,
"special": false,
"text": " for"
},
{
"id": 573,
"logprob"... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_gemma_gptq/test_flash_gemma_gptq.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_gemma_gptq/test_flash_gemma_gptq.json",
"repo_id": "text-generation-inference",
"token_count": 872
} | 255 |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [],
"seed": null,
"tokens": [
{
"id": 369,
"logprob": -2.1816406,
"special": false,
"text": " for"
},
{
"id": 279,
"logprob"... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_llama_fp8/test_flash_llama_fp8.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_llama_fp8/test_flash_llama_fp8.json",
"repo_id": "text-generation-inference",
"token_count": 862
} | 256 |
[
{
"choices": [
{
"finish_reason": "length",
"index": 0,
"logprobs": null,
"message": {
"content": "Jeff Walker's Product Launch Formula is a comprehensive system",
"name": null,
"role": "assistant",
"tool_calls": null
},
... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_llama_prefix_flashdecoding/test_flash_llama_flashdecoding.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_llama_prefix_flashdecoding/test_flash_llama_flashdecoding.json",
"repo_id": "text-generation-inference",
"token_count": 32357
} | 257 |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [],
"seed": null,
"tokens": [
{
"id": 42,
"logprob": -0.88378906,
"special": false,
"text": "I"
},
{
"id": 1353,
"logprob": ... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_neox/test_flash_neox.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_neox/test_flash_neox.json",
"repo_id": "text-generation-inference",
"token_count": 854
} | 258 |
{
"choices": [
{
"finish_reason": "stop",
"index": 0,
"logprobs": null,
"message": {
"content": "The image showcases the Statue of Liberty, a colossal bronze statue located in New York Harbor, a heritage building in the United States. The statue has a majestic presence, with one ar... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_qwen2_5_vl/test_flash_qwen2_5_vl_bay.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_qwen2_5_vl/test_flash_qwen2_5_vl_bay.json",
"repo_id": "text-generation-inference",
"token_count": 395
} | 259 |
{
"details": {
"best_of_sequences": null,
"finish_reason": "eos_token",
"generated_tokens": 9,
"prefill": [],
"seed": null,
"tokens": [
{
"id": 2684,
"logprob": -0.24902344,
"special": false,
"text": " There"
},
{
"id": 374,
"lo... | text-generation-inference/integration-tests/models/__snapshots__/test_idefics3/test_flash_idefics3_next_simple_url.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_idefics3/test_flash_idefics3_next_simple_url.json",
"repo_id": "text-generation-inference",
"token_count": 796
} | 260 |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [
{
"id": 0,
"logprob": null,
"text": "<pad>"
}
],
"seed": 0,
"tokens": [
{
"id": 16017,
"logprob": 0.0,
"special": fals... | text-generation-inference/integration-tests/models/__snapshots__/test_mt0_base/test_mt0_base_all_params.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_mt0_base/test_mt0_base_all_params.json",
"repo_id": "text-generation-inference",
"token_count": 910
} | 261 |
{
"choices": [
{
"delta": {
"content": " assistant",
"role": "assistant",
"tool_calls": null
},
"finish_reason": null,
"index": 0,
"logprobs": null
}
],
"created": 1728497531,
"id": "",
"model": "meta-llama/Llama-3.1-8B-Instruct",
"object": "chat... | text-generation-inference/integration-tests/models/__snapshots__/test_tools_llama/test_flash_llama_grammar_tools_insufficient_information_stream.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_tools_llama/test_flash_llama_grammar_tools_insufficient_information_stream.json",
"repo_id": "text-generation-inference",
"token_count": 205
} | 262 |
import pytest
import requests
@pytest.fixture(scope="module")
def llama_continue_final_message_handle(launcher):
with launcher("TinyLlama/TinyLlama-1.1B-Chat-v1.0") as handle:
yield handle
@pytest.fixture(scope="module")
async def llama_continue_final_message(llama_continue_final_message_handle):
aw... | text-generation-inference/integration-tests/models/test_continue_final_message.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_continue_final_message.py",
"repo_id": "text-generation-inference",
"token_count": 1102
} | 263 |
import pytest
@pytest.fixture(scope="module")
def flash_llama_marlin24_handle(launcher):
with launcher(
"nm-testing/Llama-2-7b-pruned2.4-Marlin_24", quantize="marlin"
) as handle:
yield handle
@pytest.fixture(scope="module")
async def flash_llama_marlin(flash_llama_marlin24_handle):
awai... | text-generation-inference/integration-tests/models/test_flash_llama_marlin_24.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_flash_llama_marlin_24.py",
"repo_id": "text-generation-inference",
"token_count": 754
} | 264 |
import pytest
@pytest.fixture(scope="module")
def flash_qwen2_vl_handle(launcher):
with launcher("Qwen/Qwen2-VL-7B-Instruct") as handle:
yield handle
@pytest.fixture(scope="module")
async def flash_qwen2(flash_qwen2_vl_handle):
await flash_qwen2_vl_handle.health(300)
return flash_qwen2_vl_handle... | text-generation-inference/integration-tests/models/test_flash_qwen2_vl.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_flash_qwen2_vl.py",
"repo_id": "text-generation-inference",
"token_count": 2158
} | 265 |
import pytest
@pytest.fixture(scope="module")
def mt0_base_handle(launcher):
with launcher("bigscience/mt0-base") as handle:
yield handle
@pytest.fixture(scope="module")
async def mt0_base(mt0_base_handle):
await mt0_base_handle.health(300)
return mt0_base_handle.client
@pytest.mark.release
@p... | text-generation-inference/integration-tests/models/test_mt0_base.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_mt0_base.py",
"repo_id": "text-generation-inference",
"token_count": 737
} | 266 |
pub fn get_cuda_capability() -> Option<(usize, usize)> {
use pyo3::prelude::*;
let py_get_capability = |py: Python| -> PyResult<(isize, isize)> {
let torch = py.import_bound("torch.cuda")?;
let get_device_capability = torch.getattr("get_device_capability")?;
get_device_capability.call0(... | text-generation-inference/launcher/src/gpu.rs/0 | {
"file_path": "text-generation-inference/launcher/src/gpu.rs",
"repo_id": "text-generation-inference",
"token_count": 350
} | 267 |
final: prev: {
# You can use this overlay to temporarily override packages for
# development. For permanent overrides, it's better to do this in
# our package flake:
#
# https://github.com/huggingface/text-generation-inference-nix
#
# Note that overriding packages that are in the transitive closure
# of... | text-generation-inference/nix/overlay.nix/0 | {
"file_path": "text-generation-inference/nix/overlay.nix",
"repo_id": "text-generation-inference",
"token_count": 597
} | 268 |
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