text stringlengths 5 409k | id stringlengths 14 178 | metadata dict | __index_level_0__ int64 0 572 |
|---|---|---|---|
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DPMSolverMultistepScheduler,
LCMScheduler,
MotionAdapter,
PIAPipeline,
StableDiffusionP... | diffusers/tests/pipelines/pia/test_pia.py/0 | {
"file_path": "diffusers/tests/pipelines/pia/test_pia.py",
"repo_id": "diffusers",
"token_count": 8145
} | 150 |
# 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_audio/test_stable_audio.py/0 | {
"file_path": "diffusers/tests/pipelines/stable_audio/test_stable_audio.py",
"repo_id": "diffusers",
"token_count": 7709
} | 151 |
# 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_attend_and_excite.py/0 | {
"file_path": "diffusers/tests/pipelines/stable_diffusion_2/test_stable_diffusion_attend_and_excite.py",
"repo_id": "diffusers",
"token_count": 4188
} | 152 |
# 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_gligen/test_stable_diffusion_gligen.py/0 | {
"file_path": "diffusers/tests/pipelines/stable_diffusion_gligen/test_stable_diffusion_gligen.py",
"repo_id": "diffusers",
"token_count": 2856
} | 153 |
# 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.py/0 | {
"file_path": "diffusers/tests/pipelines/stable_diffusion_xl/test_stable_diffusion_xl.py",
"repo_id": "diffusers",
"token_count": 20313
} | 154 |
# 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/test_pipelines_flax.py/0 | {
"file_path": "diffusers/tests/pipelines/test_pipelines_flax.py",
"repo_id": "diffusers",
"token_count": 4559
} | 155 |
The tests here are adapted from [`transformers` tests](https://github.com/huggingface/transformers/tree/409fcfdfccde77a14b7cc36972b774cabc371ae1/tests/quantization/bnb).
They were conducted on the `audace` machine, using a single RTX 4090. Below is `nvidia-smi`:
```bash
+----------------------------------------------... | diffusers/tests/quantization/bnb/README.md/0 | {
"file_path": "diffusers/tests/quantization/bnb/README.md",
"repo_id": "diffusers",
"token_count": 1033
} | 156 |
import tempfile
import torch
from diffusers import DPMSolverMultistepInverseScheduler, DPMSolverMultistepScheduler
from .test_schedulers import SchedulerCommonTest
class DPMSolverMultistepSchedulerTest(SchedulerCommonTest):
scheduler_classes = (DPMSolverMultistepInverseScheduler,)
forward_default_kwargs = ... | diffusers/tests/schedulers/test_scheduler_dpm_multi_inverse.py/0 | {
"file_path": "diffusers/tests/schedulers/test_scheduler_dpm_multi_inverse.py",
"repo_id": "diffusers",
"token_count": 5529
} | 157 |
import tempfile
import unittest
import numpy as np
import torch
from diffusers import ScoreSdeVeScheduler
class ScoreSdeVeSchedulerTest(unittest.TestCase):
# TODO adapt with class SchedulerCommonTest (scheduler needs Numpy Integration)
scheduler_classes = (ScoreSdeVeScheduler,)
forward_default_kwargs = ... | diffusers/tests/schedulers/test_scheduler_score_sde_ve.py/0 | {
"file_path": "diffusers/tests/schedulers/test_scheduler_score_sde_ve.py",
"repo_id": "diffusers",
"token_count": 3215
} | 158 |
import gc
import tempfile
import unittest
import torch
from diffusers import ControlNetModel, StableDiffusionControlNetInpaintPipeline
from diffusers.loaders.single_file_utils import _extract_repo_id_and_weights_name
from diffusers.utils import load_image
from diffusers.utils.testing_utils import (
backend_empty_... | diffusers/tests/single_file/test_stable_diffusion_controlnet_inpaint_single_file.py/0 | {
"file_path": "diffusers/tests/single_file/test_stable_diffusion_controlnet_inpaint_single_file.py",
"repo_id": "diffusers",
"token_count": 3691
} | 159 |
# coding=utf-8
# Copyright 2025 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable... | diffusers/utils/check_repo.py/0 | {
"file_path": "diffusers/utils/check_repo.py",
"repo_id": "diffusers",
"token_count": 12370
} | 160 |
# 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/update_metadata.py/0 | {
"file_path": "diffusers/utils/update_metadata.py",
"repo_id": "diffusers",
"token_count": 1709
} | 161 |
# Video benchmark
## Questions
What is the optimal trade-off between:
- maximizing loading time with random access,
- minimizing memory space on disk,
- maximizing success rate of policies,
- compatibility across devices/platforms for decoding videos (e.g. video players, web browsers).
How to encode videos?
- Which ... | lerobot/benchmarks/video/README.md/0 | {
"file_path": "lerobot/benchmarks/video/README.md",
"repo_id": "lerobot",
"token_count": 6162
} | 162 |
"""This script demonstrates how to slice a dataset and calculate the loss on a subset of the data.
This technique can be useful for debugging and testing purposes, as well as identifying whether a policy
is learning effectively.
Furthermore, relying on validation loss to evaluate performance is generally not consider... | lerobot/examples/advanced/2_calculate_validation_loss.py/0 | {
"file_path": "lerobot/examples/advanced/2_calculate_validation_loss.py",
"repo_id": "lerobot",
"token_count": 1340
} | 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/datasets/push_dataset_to_hub/xarm_pkl_format.py/0 | {
"file_path": "lerobot/lerobot/common/datasets/push_dataset_to_hub/xarm_pkl_format.py",
"repo_id": "lerobot",
"token_count": 2996
} | 164 |
#!/usr/bin/env python
# Copyright 2024 Tony Z. Zhao and The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses... | lerobot/lerobot/common/policies/act/configuration_act.py/0 | {
"file_path": "lerobot/lerobot/common/policies/act/configuration_act.py",
"repo_id": "lerobot",
"token_count": 3354
} | 165 |
#!/usr/bin/env python
# Copyright 2024 Nicklas Hansen, Xiaolong Wang, Hao Su,
# 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
#
# ht... | lerobot/lerobot/common/policies/tdmpc/modeling_tdmpc.py/0 | {
"file_path": "lerobot/lerobot/common/policies/tdmpc/modeling_tdmpc.py",
"repo_id": "lerobot",
"token_count": 17242
} | 166 |
"""Logic to calibrate a robot arm built with dynamixel motors"""
# TODO(rcadene, aliberts): move this logic into the robot code when refactoring
import numpy as np
from lerobot.common.robot_devices.motors.dynamixel import (
CalibrationMode,
TorqueMode,
convert_degrees_to_steps,
)
from lerobot.common.robot... | lerobot/lerobot/common/robot_devices/robots/dynamixel_calibration.py/0 | {
"file_path": "lerobot/lerobot/common/robot_devices/robots/dynamixel_calibration.py",
"repo_id": "lerobot",
"token_count": 2148
} | 167 |
import datetime as dt
import logging
from dataclasses import dataclass, field
from pathlib import Path
from lerobot.common import envs, policies # noqa: F401
from lerobot.common.utils.utils import auto_select_torch_device, is_amp_available, is_torch_device_available
from lerobot.configs import parser
from lerobot.con... | lerobot/lerobot/configs/eval.py/0 | {
"file_path": "lerobot/lerobot/configs/eval.py",
"repo_id": "lerobot",
"token_count": 1574
} | 168 |
#!/usr/bin/env python
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# ... | lerobot/lerobot/scripts/visualize_image_transforms.py/0 | {
"file_path": "lerobot/lerobot/scripts/visualize_image_transforms.py",
"repo_id": "lerobot",
"token_count": 1939
} | 169 |
version https://git-lfs.github.com/spec/v1
oid sha256:d8ab0274761cdd758bafdf274ce3e6398cd6f0df23393971f3e1b6b465d66ef3
size 111338
| lerobot/tests/data/save_dataset_to_safetensors/lerobot/pusht/frame_1.safetensors/0 | {
"file_path": "lerobot/tests/data/save_dataset_to_safetensors/lerobot/pusht/frame_1.safetensors",
"repo_id": "lerobot",
"token_count": 66
} | 170 |
version https://git-lfs.github.com/spec/v1
oid sha256:5dd39a554c9c3db537e98c9ceade024d172c46c4fa7ce9e27601b94116445417
size 33400
| lerobot/tests/data/save_policy_to_safetensors/aloha_act/param_stats.safetensors/0 | {
"file_path": "lerobot/tests/data/save_policy_to_safetensors/aloha_act/param_stats.safetensors",
"repo_id": "lerobot",
"token_count": 64
} | 171 |
#!/usr/bin/env python
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# ... | lerobot/tests/scripts/save_image_transforms_to_safetensors.py/0 | {
"file_path": "lerobot/tests/scripts/save_image_transforms_to_safetensors.py",
"repo_id": "lerobot",
"token_count": 1045
} | 172 |
#!/usr/bin/env python
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# ... | lerobot/tests/test_policies.py/0 | {
"file_path": "lerobot/tests/test_policies.py",
"repo_id": "lerobot",
"token_count": 8333
} | 173 |
# Model arguments
model_name_or_path: Qwen/Qwen2.5-1.5B-Instruct
model_revision: main
torch_dtype: bfloat16
attn_implementation: flash_attention_2
# Data training arguments
dataset_name: open-r1/OpenR1-Math-220k
dataset_configs:
- default
dataset_num_proc: 48
# SFT trainer config
bf16: true
do_eval: false
eval_strate... | open-r1/recipes/Qwen2.5-1.5B-Instruct/sft/config_demo.yaml/0 | {
"file_path": "open-r1/recipes/Qwen2.5-1.5B-Instruct/sft/config_demo.yaml",
"repo_id": "open-r1",
"token_count": 421
} | 174 |
#!/bin/bash
#SBATCH --job-name=r1-router
#SBATCH --partition=hopper-cpu
#SBATCH --qos=high
#SBATCH --nodes=1
#SBATCH --cpus-per-task=8
#SBATCH --mem-per-cpu=1875m
#SBATCH --output=./logs/%x_%j_%n.out
#SBATCH --error=./logs/%x_%j_%n.err
#SBATCH --time=30-00:00:00
#SBATCH --requeue
set -exuo pipefail
# TODO: Adjust the... | open-r1/slurm/serve_router.slurm/0 | {
"file_path": "open-r1/slurm/serve_router.slurm",
"repo_id": "open-r1",
"token_count": 510
} | 175 |
.PHONY: quality style test docs
check_dirs := src tests examples docs scripts docker
# Check that source code meets quality standards
# this target runs checks on all files
quality:
ruff check $(check_dirs)
ruff format --check $(check_dirs)
doc-builder style src/peft tests docs/source --max_len 119 --check_only
... | peft/Makefile/0 | {
"file_path": "peft/Makefile",
"repo_id": "peft",
"token_count": 1062
} | 176 |
<!--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/conceptual_guides/oft.md/0 | {
"file_path": "peft/docs/source/conceptual_guides/oft.md",
"repo_id": "peft",
"token_count": 2038
} | 177 |
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | peft/docs/source/package_reference/auto_class.md/0 | {
"file_path": "peft/docs/source/package_reference/auto_class.md",
"repo_id": "peft",
"token_count": 470
} | 178 |
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | peft/docs/source/package_reference/multitask_prompt_tuning.md/0 | {
"file_path": "peft/docs/source/package_reference/multitask_prompt_tuning.md",
"repo_id": "peft",
"token_count": 533
} | 179 |
<!--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/tutorial/peft_integrations.md/0 | {
"file_path": "peft/docs/source/tutorial/peft_integrations.md",
"repo_id": "peft",
"token_count": 2255
} | 180 |
<jupyter_start><jupyter_code>from transformers import AutoModelForCausalLM
from peft import get_peft_config, get_peft_model, LNTuningConfig, TaskType, PeftType
import torch
from datasets import load_dataset
import os
from transformers import AutoTokenizer
from torch.utils.data import DataLoader
from transformers import... | peft/examples/causal_language_modeling/peft_ln_tuning_clm.ipynb/0 | {
"file_path": "peft/examples/causal_language_modeling/peft_ln_tuning_clm.ipynb",
"repo_id": "peft",
"token_count": 5005
} | 181 |
<jupyter_start><jupyter_code>import os
import torch
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer, default_data_collator, get_linear_schedule_with_warmup
from peft import get_peft_model, PromptTuningConfig, TaskType, PromptTuningInit
from torch.utils.data import DataLoader
from tqdm import tqdm
from da... | peft/examples/conditional_generation/peft_prompt_tuning_seq2seq.ipynb/0 | {
"file_path": "peft/examples/conditional_generation/peft_prompt_tuning_seq2seq.ipynb",
"repo_id": "peft",
"token_count": 2336
} | 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/examples/eva_finetuning/eva_finetuning_multi_gpu.py/0 | {
"file_path": "peft/examples/eva_finetuning/eva_finetuning_multi_gpu.py",
"repo_id": "peft",
"token_count": 1356
} | 183 |
import argparse
import os
from typing import Dict
import torch
from diffusers import UNet2DConditionModel
from safetensors.torch import save_file
from transformers import CLIPTextModel
from peft import PeftModel, get_peft_model_state_dict
# Default kohya_ss LoRA replacement modules
# https://github.com/kohya-ss/sd-... | peft/examples/lora_dreambooth/convert_peft_sd_lora_to_kohya_ss.py/0 | {
"file_path": "peft/examples/lora_dreambooth/convert_peft_sd_lora_to_kohya_ss.py",
"repo_id": "peft",
"token_count": 1639
} | 184 |
<jupyter_start><jupyter_code>%env CUDA_VISIBLE_DEVICES=0
%env TOKENIZERS_PARALLELISM=false<jupyter_output>env: CUDA_VISIBLE_DEVICES=0
env: TOKENIZERS_PARALLELISM=false<jupyter_text>Initialize PolyModel<jupyter_code>import torch
from transformers import (
AutoModelForSeq2SeqLM,
AutoTokenizer,
default_data_co... | peft/examples/poly/peft_poly_seq2seq_with_generate.ipynb/0 | {
"file_path": "peft/examples/poly/peft_poly_seq2seq_with_generate.ipynb",
"repo_id": "peft",
"token_count": 4104
} | 185 |
# 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/helpers.py/0 | {
"file_path": "peft/src/peft/helpers.py",
"repo_id": "peft",
"token_count": 3455
} | 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/tuners/adalora/model.py/0 | {
"file_path": "peft/src/peft/tuners/adalora/model.py",
"repo_id": "peft",
"token_count": 7652
} | 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/src/peft/tuners/ia3/model.py/0 | {
"file_path": "peft/src/peft/tuners/ia3/model.py",
"repo_id": "peft",
"token_count": 9407
} | 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/src/peft/tuners/lora/bnb.py/0 | {
"file_path": "peft/src/peft/tuners/lora/bnb.py",
"repo_id": "peft",
"token_count": 13196
} | 189 |
# 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/multitask_prompt_tuning/config.py/0 | {
"file_path": "peft/src/peft/tuners/multitask_prompt_tuning/config.py",
"repo_id": "peft",
"token_count": 899
} | 190 |
# 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/prefix_tuning/model.py/0 | {
"file_path": "peft/src/peft/tuners/prefix_tuning/model.py",
"repo_id": "peft",
"token_count": 1228
} | 191 |
# 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/xlora/config.py/0 | {
"file_path": "peft/src/peft/tuners/xlora/config.py",
"repo_id": "peft",
"token_count": 1765
} | 192 |
# 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/regression/test_regression.py/0 | {
"file_path": "peft/tests/regression/test_regression.py",
"repo_id": "peft",
"token_count": 11016
} | 193 |
# 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_initialization.py/0 | {
"file_path": "peft/tests/test_initialization.py",
"repo_id": "peft",
"token_count": 67028
} | 194 |
# 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_xlora.py/0 | {
"file_path": "peft/tests/test_xlora.py",
"repo_id": "peft",
"token_count": 6541
} | 195 |
#!/usr/bin/env python3
""" Model Benchmark Script
An inference and train step benchmark script for timm models.
Hacked together by Ross Wightman (https://github.com/rwightman)
"""
import argparse
import csv
import json
import logging
import time
from collections import OrderedDict
from contextlib import suppress
from... | pytorch-image-models/benchmark.py/0 | {
"file_path": "pytorch-image-models/benchmark.py",
"repo_id": "pytorch-image-models",
"token_count": 13296
} | 196 |
# Big Transfer (BiT)
**Big Transfer (BiT)** is a type of pretraining recipe that pre-trains on a large supervised source dataset, and fine-tunes the weights on the target task. Models are trained on the JFT-300M dataset. The finetuned models contained in this collection are finetuned on ImageNet.
## How do I use thi... | pytorch-image-models/hfdocs/source/models/big-transfer.mdx/0 | {
"file_path": "pytorch-image-models/hfdocs/source/models/big-transfer.mdx",
"repo_id": "pytorch-image-models",
"token_count": 4103
} | 197 |
# Noisy Student (EfficientNet)
**Noisy Student Training** is a semi-supervised learning approach. It extends the idea of self-training
and distillation with the use of equal-or-larger student models and noise added to the student during learning. It has three main steps:
1. train a teacher model on labeled images
2.... | pytorch-image-models/hfdocs/source/models/noisy-student.mdx/0 | {
"file_path": "pytorch-image-models/hfdocs/source/models/noisy-student.mdx",
"repo_id": "pytorch-image-models",
"token_count": 6685
} | 198 |
# SPNASNet
**Single-Path NAS** is a novel differentiable NAS method for designing hardware-efficient ConvNets in less than 4 hours.
## How do I use this model on an image?
To load a pretrained model:
```py
>>> import timm
>>> model = timm.create_model('spnasnet_100', pretrained=True)
>>> model.eval()
```
To load a... | pytorch-image-models/hfdocs/source/models/spnasnet.mdx/0 | {
"file_path": "pytorch-image-models/hfdocs/source/models/spnasnet.mdx",
"repo_id": "pytorch-image-models",
"token_count": 1510
} | 199 |
# Optimization
This page contains the API reference documentation for learning rate optimizers included in `timm`.
## Optimizers
### Factory functions
[[autodoc]] timm.optim.create_optimizer_v2
[[autodoc]] timm.optim.list_optimizers
[[autodoc]] timm.optim.get_optimizer_class
### Optimizer Classes
[[autodoc]] timm... | pytorch-image-models/hfdocs/source/reference/optimizers.mdx/0 | {
"file_path": "pytorch-image-models/hfdocs/source/reference/optimizers.mdx",
"repo_id": "pytorch-image-models",
"token_count": 425
} | 200 |
import os
from typing import Optional
from .reader_image_folder import ReaderImageFolder
from .reader_image_in_tar import ReaderImageInTar
def create_reader(
name: str,
root: Optional[str] = None,
split: str = 'train',
**kwargs,
):
kwargs = {k: v for k, v in kwargs.items() if v is... | pytorch-image-models/timm/data/readers/reader_factory.py/0 | {
"file_path": "pytorch-image-models/timm/data/readers/reader_factory.py",
"repo_id": "pytorch-image-models",
"token_count": 694
} | 201 |
""" PyTorch selectable adaptive pooling
Adaptive pooling with the ability to select the type of pooling from:
* 'avg' - Average pooling
* 'max' - Max pooling
* 'avgmax' - Sum of average and max pooling re-scaled by 0.5
* 'avgmaxc' - Concatenation of average and max pooling along feature dim, doubles fea... | pytorch-image-models/timm/layers/adaptive_avgmax_pool.py/0 | {
"file_path": "pytorch-image-models/timm/layers/adaptive_avgmax_pool.py",
"repo_id": "pytorch-image-models",
"token_count": 3039
} | 202 |
""" NormAct (Normalization + Activation Layer) Factory
Create norm + act combo modules that attempt to be backwards compatible with separate norm + act
instances in models. Where these are used it will be possible to swap separate BN + act layers with
combined modules like IABN or EvoNorms.
Hacked together by / Copyr... | pytorch-image-models/timm/layers/create_norm_act.py/0 | {
"file_path": "pytorch-image-models/timm/layers/create_norm_act.py",
"repo_id": "pytorch-image-models",
"token_count": 1591
} | 203 |
""" Lambda Layer
Paper: `LambdaNetworks: Modeling Long-Range Interactions Without Attention`
- https://arxiv.org/abs/2102.08602
@misc{2102.08602,
Author = {Irwan Bello},
Title = {LambdaNetworks: Modeling Long-Range Interactions Without Attention},
Year = {2021},
}
Status:
This impl is a WIP. Code snippets in the... | pytorch-image-models/timm/layers/lambda_layer.py/0 | {
"file_path": "pytorch-image-models/timm/layers/lambda_layer.py",
"repo_id": "pytorch-image-models",
"token_count": 2611
} | 204 |
""" Sin-cos, fourier, rotary position embedding modules and functions
Hacked together by / Copyright 2022 Ross Wightman
"""
import math
from typing import List, Tuple, Optional, Union
import torch
from torch import nn as nn
from .grid import ndgrid
from .trace_utils import _assert
def pixel_freq_bands(
num... | pytorch-image-models/timm/layers/pos_embed_sincos.py/0 | {
"file_path": "pytorch-image-models/timm/layers/pos_embed_sincos.py",
"repo_id": "pytorch-image-models",
"token_count": 7180
} | 205 |
import torch
import torch.nn as nn
import torch.nn.functional as F
from .cross_entropy import LabelSmoothingCrossEntropy
class JsdCrossEntropy(nn.Module):
""" Jensen-Shannon Divergence + Cross-Entropy Loss
Based on impl here: https://github.com/google-research/augmix/blob/master/imagenet.py
From paper: ... | pytorch-image-models/timm/loss/jsd.py/0 | {
"file_path": "pytorch-image-models/timm/loss/jsd.py",
"repo_id": "pytorch-image-models",
"token_count": 639
} | 206 |
""" Deep Layer Aggregation and DLA w/ Res2Net
DLA original adapted from Official Pytorch impl at: https://github.com/ucbdrive/dla
DLA Paper: `Deep Layer Aggregation` - https://arxiv.org/abs/1707.06484
Res2Net additions from: https://github.com/gasvn/Res2Net/
Res2Net Paper: `Res2Net: A New Multi-scale Backbone Architec... | pytorch-image-models/timm/models/dla.py/0 | {
"file_path": "pytorch-image-models/timm/models/dla.py",
"repo_id": "pytorch-image-models",
"token_count": 9163
} | 207 |
from functools import partial
import torch.nn as nn
from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
from ._builder import build_model_with_cfg
from ._builder import pretrained_cfg_for_features
from ._efficientnet_blocks import SqueezeExcite
from ._efficientnet_builder import decode_arch_def, resolve... | pytorch-image-models/timm/models/hardcorenas.py/0 | {
"file_path": "pytorch-image-models/timm/models/hardcorenas.py",
"repo_id": "pytorch-image-models",
"token_count": 4629
} | 208 |
""" MLP-Mixer, ResMLP, and gMLP in PyTorch
This impl originally based on MLP-Mixer paper.
Official JAX impl: https://github.com/google-research/vision_transformer/blob/linen/vit_jax/models_mixer.py
Paper: 'MLP-Mixer: An all-MLP Architecture for Vision' - https://arxiv.org/abs/2105.01601
@article{tolstikhin2021,
t... | pytorch-image-models/timm/models/mlp_mixer.py/0 | {
"file_path": "pytorch-image-models/timm/models/mlp_mixer.py",
"repo_id": "pytorch-image-models",
"token_count": 13020
} | 209 |
""" Res2Net and Res2NeXt
Adapted from Official Pytorch impl at: https://github.com/gasvn/Res2Net/
Paper: `Res2Net: A New Multi-scale Backbone Architecture` - https://arxiv.org/abs/1904.01169
"""
import math
import torch
import torch.nn as nn
from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
from ._bui... | pytorch-image-models/timm/models/res2net.py/0 | {
"file_path": "pytorch-image-models/timm/models/res2net.py",
"repo_id": "pytorch-image-models",
"token_count": 3659
} | 210 |
"""VGG
Adapted from https://github.com/pytorch/vision 'vgg.py' (BSD-3-Clause) with a few changes for
timm functionality.
Copyright 2021 Ross Wightman
"""
from typing import Any, Dict, List, Optional, Type, Union, cast
import torch
import torch.nn as nn
import torch.nn.functional as F
from timm.data import IMAGENET_... | pytorch-image-models/timm/models/vgg.py/0 | {
"file_path": "pytorch-image-models/timm/models/vgg.py",
"repo_id": "pytorch-image-models",
"token_count": 5197
} | 211 |
import math
import torch
from torch.optim.optimizer import Optimizer
class AdaBelief(Optimizer):
r"""Implements AdaBelief algorithm. Modified from Adam in PyTorch
Arguments:
params (iterable): iterable of parameters to optimize or dicts defining
parameter groups
lr (float, optiona... | pytorch-image-models/timm/optim/adabelief.py/0 | {
"file_path": "pytorch-image-models/timm/optim/adabelief.py",
"repo_id": "pytorch-image-models",
"token_count": 5278
} | 212 |
import math
import torch
from torch.optim.optimizer import Optimizer
class NAdamLegacy(Optimizer):
"""Implements Nadam algorithm (a variant of Adam based on Nesterov momentum).
NOTE: This impl has been deprecated in favour of torch.optim.NAdam and remains as a reference
It has been proposed in `Incorpo... | pytorch-image-models/timm/optim/nadam.py/0 | {
"file_path": "pytorch-image-models/timm/optim/nadam.py",
"repo_id": "pytorch-image-models",
"token_count": 2021
} | 213 |
""" Step Scheduler
Basic step LR schedule with warmup, noise.
Hacked together by / Copyright 2020 Ross Wightman
"""
import math
import torch
from typing import List
from .scheduler import Scheduler
class StepLRScheduler(Scheduler):
"""
"""
def __init__(
self,
optimizer: torch.... | pytorch-image-models/timm/scheduler/step_lr.py/0 | {
"file_path": "pytorch-image-models/timm/scheduler/step_lr.py",
"repo_id": "pytorch-image-models",
"token_count": 951
} | 214 |
from typing import Optional, Tuple, List
import torch
def onnx_forward(onnx_file, example_input):
import onnxruntime
sess_options = onnxruntime.SessionOptions()
session = onnxruntime.InferenceSession(onnx_file, sess_options)
input_name = session.get_inputs()[0].name
output = session.run([], {inp... | pytorch-image-models/timm/utils/onnx.py/0 | {
"file_path": "pytorch-image-models/timm/utils/onnx.py",
"repo_id": "pytorch-image-models",
"token_count": 1722
} | 215 |
<!---
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 ... | smolagents/README.md/0 | {
"file_path": "smolagents/README.md",
"repo_id": "smolagents",
"token_count": 3903
} | 216 |
<!--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/inspect_runs.mdx/0 | {
"file_path": "smolagents/docs/source/en/tutorials/inspect_runs.mdx",
"repo_id": "smolagents",
"token_count": 2410
} | 217 |
<!--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/tutorials/inspect_runs.mdx/0 | {
"file_path": "smolagents/docs/source/hi/tutorials/inspect_runs.mdx",
"repo_id": "smolagents",
"token_count": 3439
} | 218 |
<!--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/tutorials/secure_code_execution.mdx/0 | {
"file_path": "smolagents/docs/source/zh/tutorials/secure_code_execution.mdx",
"repo_id": "smolagents",
"token_count": 2729
} | 219 |
import re
import string
import warnings
def normalize_number_str(number_str: str) -> float:
# we replace these common units and commas to allow
# conversion to float
for char in ["$", "%", ","]:
number_str = number_str.replace(char, "")
try:
return float(number_str)
except ValueErr... | smolagents/examples/open_deep_research/scripts/gaia_scorer.py/0 | {
"file_path": "smolagents/examples/open_deep_research/scripts/gaia_scorer.py",
"repo_id": "smolagents",
"token_count": 1643
} | 220 |
#!/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/L... | smolagents/src/smolagents/cli.py/0 | {
"file_path": "smolagents/src/smolagents/cli.py",
"repo_id": "smolagents",
"token_count": 1783
} | 221 |
# 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_types.py/0 | {
"file_path": "smolagents/tests/test_types.py",
"repo_id": "smolagents",
"token_count": 1522
} | 222 |
[package]
name = "grpc-metadata"
version = "0.1.0"
edition = "2021"
[dependencies]
opentelemetry = "^0.20"
tonic = "^0.10"
tracing = "^0.1"
tracing-opentelemetry = "^0.21"
| text-generation-inference/backends/grpc-metadata/Cargo.toml/0 | {
"file_path": "text-generation-inference/backends/grpc-metadata/Cargo.toml",
"repo_id": "text-generation-inference",
"token_count": 83
} | 223 |
import copy
import logging
import time
from abc import ABC
from enum import Enum
from typing import List, Optional, Tuple
import torch
from loguru import logger
from transformers import AutoConfig, AutoTokenizer, PreTrainedTokenizerBase
from transformers.generation import GenerationConfig
from optimum.neuron import N... | text-generation-inference/backends/neuron/server/text_generation_server/generator.py/0 | {
"file_path": "text-generation-inference/backends/neuron/server/text_generation_server/generator.py",
"repo_id": "text-generation-inference",
"token_count": 11513
} | 224 |
#!/usr/bin/env python
import argparse
import logging
import os
import sys
from typing import Any, Dict, List, Optional
from huggingface_hub import constants
from transformers import AutoConfig
from optimum.neuron.modeling_decoder import get_available_cores
from optimum.neuron.utils import get_hub_cached_entries
from... | text-generation-inference/backends/neuron/tgi_env.py/0 | {
"file_path": "text-generation-inference/backends/neuron/tgi_env.py",
"repo_id": "text-generation-inference",
"token_count": 3461
} | 225 |
pub use looper::TensorRtLlmBackendV2;
pub mod errors;
mod looper;
mod utils;
#[cxx::bridge(namespace = "huggingface::tgi::backends::trtllm")]
mod ffi {
#[cxx_name = "finish_reason_t"]
#[derive(Debug, Clone, Copy)]
pub enum FinishReason {
/// The request is not finished.
#[cxx_name = "kNOT_... | text-generation-inference/backends/trtllm/src/lib.rs/0 | {
"file_path": "text-generation-inference/backends/trtllm/src/lib.rs",
"repo_id": "text-generation-inference",
"token_count": 1463
} | 226 |
use std::sync::Arc;
use criterion::{black_box, criterion_group, criterion_main, Criterion};
use rand::Rng;
use text_generation_router_v3::block_allocator::Allocator;
use text_generation_router_v3::radix::RadixAllocator;
fn prefix_cache_benchmark(c: &mut Criterion) {
// let prefixes: Vec<Vec<u32>> = (0..8192)
... | text-generation-inference/backends/v3/benches/prefix_cache.rs/0 | {
"file_path": "text-generation-inference/backends/v3/benches/prefix_cache.rs",
"repo_id": "text-generation-inference",
"token_count": 806
} | 227 |
mod app;
mod event;
mod generation;
mod table;
mod utils;
use crate::app::App;
use crate::event::Event;
use ratatui::backend::CrosstermBackend;
use ratatui::crossterm::ExecutableCommand;
use ratatui::Terminal;
use std::io;
use text_generation_client::v3::{GrammarType, NextTokenChooserParameters, ShardedClient};
use to... | text-generation-inference/benchmark/src/lib.rs/0 | {
"file_path": "text-generation-inference/benchmark/src/lib.rs",
"repo_id": "text-generation-inference",
"token_count": 1979
} | 228 |
from typing import Dict
# Text Generation Inference Errors
class ValidationError(Exception):
def __init__(self, message: str):
super().__init__(message)
class GenerationError(Exception):
def __init__(self, message: str):
super().__init__(message)
class OverloadedError(Exception):
def _... | text-generation-inference/clients/python/text_generation/errors.py/0 | {
"file_path": "text-generation-inference/clients/python/text_generation/errors.py",
"repo_id": "text-generation-inference",
"token_count": 1080
} | 229 |
# Tensor Parallelism
Tensor parallelism is a technique used to fit a large model in multiple GPUs. For example, when multiplying the input tensors with the first weight tensor, the matrix multiplication is equivalent to splitting the weight tensor column-wise, multiplying each column with the input separately, and the... | text-generation-inference/docs/source/conceptual/tensor_parallelism.md/0 | {
"file_path": "text-generation-inference/docs/source/conceptual/tensor_parallelism.md",
"repo_id": "text-generation-inference",
"token_count": 272
} | 230 |
{
"nodes": {
"cachix": {
"inputs": {
"devenv": ["crate2nix"],
"flake-compat": ["crate2nix"],
"nixpkgs": "nixpkgs",
"pre-commit-hooks": ["crate2nix"]
},
"locked": {
"lastModified": 1709700175,
"narHash": "sha256-A0/6ZjLmT9qdYzKHmevnEIC7G+GiZ4UCr8v0p... | text-generation-inference/flake.lock/0 | {
"file_path": "text-generation-inference/flake.lock",
"repo_id": "text-generation-inference",
"token_count": 15873
} | 231 |
{
"choices": [
{
"finish_reason": "length",
"index": 0,
"logprobs": null,
"text": " A Beginner’s Guide\nDeep learning is a subset"
}
],
"created": 1725876621,
"id": "",
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "2.2... | text-generation-inference/integration-tests/models/__snapshots__/test_completion_prompts/test_flash_llama_completion_single_prompt.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_completion_prompts/test_flash_llama_completion_single_prompt.json",
"repo_id": "text-generation-inference",
"token_count": 212
} | 232 |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [],
"seed": null,
"tokens": [
{
"id": 25,
"logprob": -2.9316406,
"special": false,
"text": ":"
},
{
"id": 330,
"logprob": -3... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_llama_exl2/test_flash_llama_exl2.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_llama_exl2/test_flash_llama_exl2.json",
"repo_id": "text-generation-inference",
"token_count": 880
} | 233 |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [],
"seed": 0,
"tokens": [
{
"id": 5229,
"logprob": -0.6645508,
"special": false,
"text": " failed"
},
{
"id": 29901,
"logpr... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_llama_marlin_24/test_flash_llama_marlin24_all_params.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_llama_marlin_24/test_flash_llama_marlin24_all_params.json",
"repo_id": "text-generation-inference",
"token_count": 857
} | 234 |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [],
"seed": null,
"tokens": [
{
"id": 198,
"logprob": -2.9023438,
"special": false,
"text": "\n"
},
{
"id": 2,
"logprob": -2... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_qwen2/test_flash_qwen2.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_qwen2/test_flash_qwen2.json",
"repo_id": "text-generation-inference",
"token_count": 865
} | 235 |
[
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [],
"seed": null,
"tokens": [
{
"id": 330,
"logprob": -0.09289551,
"special": false,
"text": " A"
},
{
... | text-generation-inference/integration-tests/models/__snapshots__/test_idefics2/test_flash_idefics2_next_load.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_idefics2/test_flash_idefics2_next_load.json",
"repo_id": "text-generation-inference",
"token_count": 4039
} | 236 |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 17,
"prefill": [
{
"id": 1276,
"logprob": null,
"text": "What"
},
{
"id": 310,
"logprob": -1.5117188,
"text": " is"
},
{
"id": ... | text-generation-inference/integration-tests/models/__snapshots__/test_mpt/test_mpt.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_mpt/test_mpt.json",
"repo_id": "text-generation-inference",
"token_count": 1691
} | 237 |
import pytest
@pytest.fixture(scope="module")
def compressed_tensors_w8an_handle(launcher):
with launcher(
"neuralmagic/Llama-3.2-1B-Instruct-FP8",
num_shard=2,
quantize="compressed-tensors",
) as handle:
yield handle
@pytest.fixture(scope="module")
async def compressed_tenso... | text-generation-inference/integration-tests/models/test_compressed_tensors_w8an_fp.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_compressed_tensors_w8an_fp.py",
"repo_id": "text-generation-inference",
"token_count": 1000
} | 238 |
import pytest
@pytest.fixture(scope="module")
def flash_llama_fp8_kv_cache_handle(launcher):
with launcher(
"neuralmagic/Meta-Llama-3-8B-Instruct-FP8-KV",
num_shard=2,
kv_cache_dtype="fp8_e4m3fn",
) as handle:
yield handle
@pytest.fixture(scope="module")
async def flash_llama... | text-generation-inference/integration-tests/models/test_flash_llama_fp8_kv_cache.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_flash_llama_fp8_kv_cache.py",
"repo_id": "text-generation-inference",
"token_count": 986
} | 239 |
import pytest
@pytest.fixture(scope="module")
def flash_phi35_moe_handle(launcher):
with launcher(
"microsoft/Phi-3.5-MoE-instruct",
num_shard=4,
) as handle:
yield handle
@pytest.fixture(scope="module")
async def flash_phi35_moe(flash_phi35_moe_handle):
await flash_phi35_moe_han... | text-generation-inference/integration-tests/models/test_flash_phi35_moe.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_flash_phi35_moe.py",
"repo_id": "text-generation-inference",
"token_count": 921
} | 240 |
import pytest
@pytest.fixture(scope="module")
def fused_kernel_mamba_handle(launcher):
with launcher("state-spaces/mamba-130m-hf", num_shard=1) as handle:
yield handle
@pytest.fixture(scope="module")
async def fused_kernel_mamba(fused_kernel_mamba_handle):
await fused_kernel_mamba_handle.health(300)... | text-generation-inference/integration-tests/models/test_mamba.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_mamba.py",
"repo_id": "text-generation-inference",
"token_count": 825
} | 241 |
[package]
name = "text-generation-launcher"
description = "Text Generation Launcher"
version.workspace = true
edition.workspace = true
authors.workspace = true
homepage.workspace = true
[dependencies]
clap = { version = "4.4.5", features = ["derive", "env"] }
ctrlc = { version = "3.4.1", features = ["termination"] }
h... | text-generation-inference/launcher/Cargo.toml/0 | {
"file_path": "text-generation-inference/launcher/Cargo.toml",
"repo_id": "text-generation-inference",
"token_count": 343
} | 242 |
{ pkgs, nix-filter }:
let
filter = nix-filter.lib;
in
with pkgs;
defaultCrateOverrides
// {
aws-lc-rs = attrs: {
# aws-lc-rs does its own custom parsing of Cargo environment
# variables like DEP_.*_INCLUDE. However buildRustCrate does
# not use the version number, so the parsing fails.
postPatch = ... | text-generation-inference/nix/crate-overrides.nix/0 | {
"file_path": "text-generation-inference/nix/crate-overrides.nix",
"repo_id": "text-generation-inference",
"token_count": 937
} | 243 |
use opentelemetry::sdk::propagation::TraceContextPropagator;
use opentelemetry::sdk::trace;
use opentelemetry::sdk::trace::Sampler;
use opentelemetry::sdk::Resource;
use opentelemetry::{global, KeyValue};
use opentelemetry_otlp::WithExportConfig;
use tracing_subscriber::layer::SubscriberExt;
use tracing_subscriber::uti... | text-generation-inference/router/src/logging.rs/0 | {
"file_path": "text-generation-inference/router/src/logging.rs",
"repo_id": "text-generation-inference",
"token_count": 1445
} | 244 |
lorax_punica_commit := c71861a653412267dc27ec86013dd945ce3474bc
build-lorax-punica:
if [ ! -d 'lorax-punica' ]; then \
git clone --no-checkout https://github.com/predibase/lorax.git lorax-punica; \
fi
cd lorax-punica && git sparse-checkout set server/punica_kernels && git checkout $(lorax_punica_commit)
cd lorax... | text-generation-inference/server/Makefile-lorax-punica/0 | {
"file_path": "text-generation-inference/server/Makefile-lorax-punica",
"repo_id": "text-generation-inference",
"token_count": 208
} | 245 |
// Adapted from turboderp exllama: https://github.com/turboderp/exllama
#ifndef _q4_matrix_cuh
#define _q4_matrix_cuh
#include <cuda_runtime.h>
#include <cuda_fp16.h>
#include <cstdint>
class Q4Matrix
{
public:
int device;
int height;
int width;
int groups;
int groupsize;
uint32_t* cuda_qw... | text-generation-inference/server/exllama_kernels/exllama_kernels/cuda_func/q4_matrix.cuh/0 | {
"file_path": "text-generation-inference/server/exllama_kernels/exllama_kernels/cuda_func/q4_matrix.cuh",
"repo_id": "text-generation-inference",
"token_count": 420
} | 246 |
#ifndef _q_matrix_cuh
#define _q_matrix_cuh
#include <cuda_runtime.h>
#include <cuda_fp16.h>
#include <cstdint>
#include <cstdio>
#define MAX_SUPERGROUPS 16
class QMatrix
{
public:
int device;
bool is_gptq;
int height;
int width;
int groups;
int gptq_groupsize;
int rows_8;
int rows... | text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/q_matrix.cuh/0 | {
"file_path": "text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/q_matrix.cuh",
"repo_id": "text-generation-inference",
"token_count": 702
} | 247 |
# Origin: https://github.com/predibase/lorax
# Path: lorax/server/lorax_server/adapters/__init__.py
# License: Apache License Version 2.0, January 2004
from text_generation_server.adapters.weights import (
AdapterBatchData,
AdapterBatchMetadata,
)
__all__ = [
"AdapterBatchData",
"AdapterBatchMe... | text-generation-inference/server/text_generation_server/adapters/__init__.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/adapters/__init__.py",
"repo_id": "text-generation-inference",
"token_count": 125
} | 248 |
import torch
from typing import List
AWQ_PACK_ORDER = [0, 2, 4, 6, 1, 3, 5, 7]
REVERSE_AWQ_PACK_ORDER = [0, 4, 1, 5, 2, 6, 3, 7]
def pack(imatrix: torch.Tensor, direction: str = "column"):
"""
Packs a 4-bit integer matrix into a packed 32-bit integer matrix.
Args:
imatrix (torch.Tensor): matrix ... | text-generation-inference/server/text_generation_server/layers/awq/conversion_utils.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/layers/awq/conversion_utils.py",
"repo_id": "text-generation-inference",
"token_count": 1384
} | 249 |
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