text stringlengths 5 424k | id stringlengths 13 178 | metadata dict | __index_level_0__ int64 0 672 |
|---|---|---|---|
accelerate launch --config_file "configs/deepspeed_config.yaml" train.py \
--seed 100 \
--model_name_or_path "meta-llama/Llama-2-70b-hf" \
--dataset_name "smangrul/ultrachat-10k-chatml" \
--chat_template_format "chatml" \
--add_special_tokens False \
--append_concat_token False \
--splits "train,test" \
--max_seq_len ... | peft/examples/sft/run_peft_deepspeed.sh/0 | {
"file_path": "peft/examples/sft/run_peft_deepspeed.sh",
"repo_id": "peft",
"token_count": 453
} | 269 |
{
"auto_mapping": null,
"base_model_name_or_path": null,
"bias": "none",
"exclude_modules": null,
"fan_in_fan_out": false,
"inference_mode": false,
"init_weights": false,
"layers_pattern": null,
"layers_to_transform": null,
"modules_to_save": null,
"n_frequency": 1000,
"n_frequency_pattern": {},... | peft/method_comparison/MetaMathQA/experiments/fourierft/llama-3.2-3B-default/adapter_config.json/0 | {
"file_path": "peft/method_comparison/MetaMathQA/experiments/fourierft/llama-3.2-3B-default/adapter_config.json",
"repo_id": "peft",
"token_count": 213
} | 270 |
{
"auto_mapping": null,
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"bias": "none",
"exclude_modules": null,
"inference_mode": false,
"init_weights": true,
"layers_pattern": null,
"layers_to_transform": null,
"mini_r": 1,
"miss_dropout": 0.0,
"modules_to_save": null,
"peft_type": "MISS",
"r": 64,
"revi... | peft/method_comparison/MetaMathQA/experiments/miss/llama-3.2-3B-default/adapter_config.json/0 | {
"file_path": "peft/method_comparison/MetaMathQA/experiments/miss/llama-3.2-3B-default/adapter_config.json",
"repo_id": "peft",
"token_count": 164
} | 271 |
{
"auto_mapping": null,
"base_model_name_or_path": null,
"bias": "none",
"exclude_modules": null,
"fan_in_fan_out": false,
"inference_mode": false,
"init_logits_std": 0.1,
"init_vector_bank_bound": 0.02,
"layers_pattern": null,
"layers_to_transform": null,
"modules_to_save": null,
"num_vectors":... | peft/method_comparison/MetaMathQA/experiments/vblora/llama-3.2-3B-default/adapter_config.json/0 | {
"file_path": "peft/method_comparison/MetaMathQA/experiments/vblora/llama-3.2-3B-default/adapter_config.json",
"repo_id": "peft",
"token_count": 255
} | 272 |
# Copyright 2023 The HuggingFace Team, the AllenNLP library authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
... | peft/scripts/stale.py/0 | {
"file_path": "peft/scripts/stale.py",
"repo_id": "peft",
"token_count": 890
} | 273 |
# 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
} | 274 |
# 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": 2005
} | 275 |
# 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/corda.py/0 | {
"file_path": "peft/src/peft/tuners/lora/corda.py",
"repo_id": "peft",
"token_count": 6533
} | 276 |
# 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/miss/model.py/0 | {
"file_path": "peft/src/peft/tuners/miss/model.py",
"repo_id": "peft",
"token_count": 2082
} | 277 |
# 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/model.py/0 | {
"file_path": "peft/src/peft/tuners/oft/model.py",
"repo_id": "peft",
"token_count": 3449
} | 278 |
# 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 applicable law or... | peft/src/peft/tuners/randlora/bnb.py/0 | {
"file_path": "peft/src/peft/tuners/randlora/bnb.py",
"repo_id": "peft",
"token_count": 9574
} | 279 |
# 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 applicable law or... | peft/src/peft/tuners/trainable_tokens/layer.py/0 | {
"file_path": "peft/src/peft/tuners/trainable_tokens/layer.py",
"repo_id": "peft",
"token_count": 4552
} | 280 |
# 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/model.py/0 | {
"file_path": "peft/src/peft/tuners/xlora/model.py",
"repo_id": "peft",
"token_count": 9281
} | 281 |
# 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": 10766
} | 282 |
# Copyright 2023-present the HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or... | peft/tests/test_hub_features.py/0 | {
"file_path": "peft/tests/test_hub_features.py",
"repo_id": "peft",
"token_count": 4321
} | 283 |
# 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 applicable law or... | peft/tests/test_shira.py/0 | {
"file_path": "peft/tests/test_shira.py",
"repo_id": "peft",
"token_count": 5860
} | 284 |
- sections:
- local: index
title: Home
- local: quickstart
title: Quickstart
- local: installation
title: Installation
- local: changes
title: Changelog
title: Get started
- sections:
- local: feature_extraction
title: Using Pretrained Models as Feature Extractors
- local: training_sc... | pytorch-image-models/hfdocs/source/_toctree.yml/0 | {
"file_path": "pytorch-image-models/hfdocs/source/_toctree.yml",
"repo_id": "pytorch-image-models",
"token_count": 1701
} | 285 |
# Inception v4
**Inception-v4** is a convolutional neural network architecture that builds on previous iterations of the Inception family by simplifying the architecture and using more inception modules than [Inception-v3](https://paperswithcode.com/method/inception-v3).
## How do I use this model on an image?
To loa... | pytorch-image-models/hfdocs/source/models/inception-v4.mdx/0 | {
"file_path": "pytorch-image-models/hfdocs/source/models/inception-v4.mdx",
"repo_id": "pytorch-image-models",
"token_count": 1628
} | 286 |
# ResNet-D
**ResNet-D** is a modification on the [ResNet](https://paperswithcode.com/method/resnet) architecture that utilises an [average pooling](https://paperswithcode.com/method/average-pooling) tweak for downsampling. The motivation is that in the unmodified ResNet, the [1×1 convolution](https://paperswithcode.co... | pytorch-image-models/hfdocs/source/models/resnet-d.mdx/0 | {
"file_path": "pytorch-image-models/hfdocs/source/models/resnet-d.mdx",
"repo_id": "pytorch-image-models",
"token_count": 3935
} | 287 |
""" ONNX-runtime validation script
This script was created to verify accuracy and performance of exported ONNX
models running with the onnxruntime. It utilizes the PyTorch dataloader/processing
pipeline for a fair comparison against the originals.
Copyright 2020 Ross Wightman
"""
import argparse
import numpy as np
im... | pytorch-image-models/onnx_validate.py/0 | {
"file_path": "pytorch-image-models/onnx_validate.py",
"repo_id": "pytorch-image-models",
"token_count": 1960
} | 288 |
"""Run tests for all models
Tests that run on CI should have a specific marker, e.g. @pytest.mark.base. This
marker is used to parallelize the CI runs, with one runner for each marker.
If new tests are added, ensure that they use one of the existing markers
(documented in pyproject.toml > pytest > markers) or that a ... | pytorch-image-models/tests/test_models.py/0 | {
"file_path": "pytorch-image-models/tests/test_models.py",
"repo_id": "pytorch-image-models",
"token_count": 13671
} | 289 |
import math
import torch
from torch.utils.data import Sampler
import torch.distributed as dist
class OrderedDistributedSampler(Sampler):
"""Sampler that restricts data loading to a subset of the dataset.
It is especially useful in conjunction with
:class:`torch.nn.parallel.DistributedDataParallel`. In suc... | pytorch-image-models/timm/data/distributed_sampler.py/0 | {
"file_path": "pytorch-image-models/timm/data/distributed_sampler.py",
"repo_id": "pytorch-image-models",
"token_count": 2276
} | 290 |
""" Dataset reader for HF IterableDataset
"""
import math
import os
from itertools import repeat, chain
from typing import Optional
import torch
import torch.distributed as dist
from PIL import Image
try:
import datasets
from datasets.distributed import split_dataset_by_node
from datasets.splits import Sp... | pytorch-image-models/timm/data/readers/reader_hfids.py/0 | {
"file_path": "pytorch-image-models/timm/data/readers/reader_hfids.py",
"repo_id": "pytorch-image-models",
"token_count": 3798
} | 291 |
from typing import Final, Optional, Type
import torch
from torch import nn as nn
from torch.nn import functional as F
from ._fx import register_notrace_function
from .config import use_fused_attn
from .pos_embed_sincos import apply_rot_embed_cat
@torch.fx.wrap
@register_notrace_function
def maybe_add_mask(scores: t... | pytorch-image-models/timm/layers/attention.py/0 | {
"file_path": "pytorch-image-models/timm/layers/attention.py",
"repo_id": "pytorch-image-models",
"token_count": 4345
} | 292 |
""" 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": 2027
} | 293 |
""" 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
} | 294 |
""" Relative position embedding modules and functions
Hacked together by / Copyright 2022 Ross Wightman
"""
import math
import os
from typing import Optional, Tuple
import torch
import torch.nn as nn
import torch.nn.functional as F
from .grid import ndgrid
from .interpolate import RegularGridInterpolator
from .mlp i... | pytorch-image-models/timm/layers/pos_embed_rel.py/0 | {
"file_path": "pytorch-image-models/timm/layers/pos_embed_rel.py",
"repo_id": "pytorch-image-models",
"token_count": 9303
} | 295 |
""" Cross Entropy w/ smoothing or soft targets
Hacked together by / Copyright 2021 Ross Wightman
"""
import torch
import torch.nn as nn
import torch.nn.functional as F
class LabelSmoothingCrossEntropy(nn.Module):
""" NLL loss with label smoothing.
"""
def __init__(self, smoothing=0.1):
super(Lab... | pytorch-image-models/timm/loss/cross_entropy.py/0 | {
"file_path": "pytorch-image-models/timm/loss/cross_entropy.py",
"repo_id": "pytorch-image-models",
"token_count": 470
} | 296 |
"""Pytorch Densenet implementation w/ tweaks
This file is a copy of https://github.com/pytorch/vision 'densenet.py' (BSD-3-Clause) with
fixed kwargs passthrough and addition of dynamic global avg/max pool.
"""
import re
from collections import OrderedDict
from typing import Any, Dict, Optional, Tuple, Union
import tor... | pytorch-image-models/timm/models/densenet.py/0 | {
"file_path": "pytorch-image-models/timm/models/densenet.py",
"repo_id": "pytorch-image-models",
"token_count": 9539
} | 297 |
""" Global Context ViT
From scratch implementation of GCViT in the style of timm swin_transformer_v2_cr.py
Global Context Vision Transformers -https://arxiv.org/abs/2206.09959
@article{hatamizadeh2022global,
title={Global Context Vision Transformers},
author={Hatamizadeh, Ali and Yin, Hongxu and Kautz, Jan and M... | pytorch-image-models/timm/models/gcvit.py/0 | {
"file_path": "pytorch-image-models/timm/models/gcvit.py",
"repo_id": "pytorch-image-models",
"token_count": 11844
} | 298 |
""" MaxVit and CoAtNet Vision Transformer - CNN Hybrids in PyTorch
This is a from-scratch implementation of both CoAtNet and MaxVit in PyTorch.
99% of the implementation was done from papers, however last minute some adjustments were made
based on the (as yet unfinished?) public code release https://github.com/google... | pytorch-image-models/timm/models/maxxvit.py/0 | {
"file_path": "pytorch-image-models/timm/models/maxxvit.py",
"repo_id": "pytorch-image-models",
"token_count": 48676
} | 299 |
""" Swin Transformer
A PyTorch impl of : `Swin Transformer: Hierarchical Vision Transformer using Shifted Windows`
- https://arxiv.org/pdf/2103.14030
Code/weights from https://github.com/microsoft/Swin-Transformer, original copyright/license info below
S3 (AutoFormerV2, https://arxiv.org/abs/2111.14725) Swin weig... | pytorch-image-models/timm/models/swin_transformer.py/0 | {
"file_path": "pytorch-image-models/timm/models/swin_transformer.py",
"repo_id": "pytorch-image-models",
"token_count": 22338
} | 300 |
"""
Ported to pytorch thanks to [tstandley](https://github.com/tstandley/Xception-PyTorch)
@author: tstandley
Adapted by cadene
Creates an Xception Model as defined in:
Francois Chollet
Xception: Deep Learning with Depthwise Separable Convolutions
https://arxiv.org/pdf/1610.02357.pdf
This weights ported from the Ke... | pytorch-image-models/timm/models/xception.py/0 | {
"file_path": "pytorch-image-models/timm/models/xception.py",
"repo_id": "pytorch-image-models",
"token_count": 3992
} | 301 |
""" PyTorch Lamb optimizer w/ behaviour similar to NVIDIA FusedLamb
This optimizer code was adapted from the following (starting with latest)
* https://github.com/HabanaAI/Model-References/blob/2b435114fe8e31f159b1d3063b8280ae37af7423/PyTorch/nlp/bert/pretraining/lamb.py
* https://github.com/NVIDIA/DeepLearningExample... | pytorch-image-models/timm/optim/lamb.py/0 | {
"file_path": "pytorch-image-models/timm/optim/lamb.py",
"repo_id": "pytorch-image-models",
"token_count": 4651
} | 302 |
from .cosine_lr import CosineLRScheduler
from .multistep_lr import MultiStepLRScheduler
from .plateau_lr import PlateauLRScheduler
from .poly_lr import PolyLRScheduler
from .step_lr import StepLRScheduler
from .tanh_lr import TanhLRScheduler
from .scheduler_factory import create_scheduler, create_scheduler_v2, schedul... | pytorch-image-models/timm/scheduler/__init__.py/0 | {
"file_path": "pytorch-image-models/timm/scheduler/__init__.py",
"repo_id": "pytorch-image-models",
"token_count": 112
} | 303 |
""" Distributed training/validation utils
Hacked together by / Copyright 2020 Ross Wightman
"""
import logging
import os
from typing import Optional
import torch
from torch import distributed as dist
from .model import unwrap_model
_logger = logging.getLogger(__name__)
def reduce_tensor(tensor, n):
rt = tenso... | pytorch-image-models/timm/utils/distributed.py/0 | {
"file_path": "pytorch-image-models/timm/utils/distributed.py",
"repo_id": "pytorch-image-models",
"token_count": 2680
} | 304 |
# Human-in-the-Loop: Customize Agent Plan Interactively
This page demonstrates advanced usage of the smolagents library, with a special focus on **Human-in-the-Loop (HITL)** approaches for interactive plan creation, user-driven plan modification, and memory preservation in agentic workflows.
The example is based on th... | smolagents/docs/source/en/examples/plan_customization.md/0 | {
"file_path": "smolagents/docs/source/en/examples/plan_customization.md",
"repo_id": "smolagents",
"token_count": 996
} | 305 |
# Tools
[[open-in-colab]]
Here, we're going to see advanced tool usage.
> [!TIP]
> If you're new to building agents, make sure to first read the [intro to agents](../conceptual_guides/intro_agents) and the [guided tour of smolagents](../guided_tour).
### What is a tool, and how to build one?
A tool is mostly a fu... | smolagents/docs/source/en/tutorials/tools.md/0 | {
"file_path": "smolagents/docs/source/en/tutorials/tools.md",
"repo_id": "smolagents",
"token_count": 5412
} | 306 |
# 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/ko/_config.py/0 | {
"file_path": "smolagents/docs/source/ko/_config.py",
"repo_id": "smolagents",
"token_count": 155
} | 307 |
# 使用Agent实现网页浏览器自动化 🤖🌐
[[open-in-colab]]
在本notebook中，我们将创建一个**基于Agent的网页浏览器自动化系统**！该系统可以自动导航网站、与网页元素交互并提取信息。
该Agent将能够：
- [x] 导航到网页
- [x] 点击元素
- [x] 在页面内搜索
- [x] 处理弹出窗口和模态框
- [x] 提取信息
让我们一步步搭建这个系统！
首先运行以下命令安装所需依赖：
```bash
pip install smolagents selenium helium pillow -q
```
让我们导入所需的库并设置环境变量：
```python
from i... | smolagents/docs/source/zh/examples/web_browser.md/0 | {
"file_path": "smolagents/docs/source/zh/examples/web_browser.md",
"repo_id": "smolagents",
"token_count": 2742
} | 308 |
from smolagents import CodeAgent, GradioUI, InferenceClientModel, WebSearchTool
agent = CodeAgent(
tools=[WebSearchTool()],
model=InferenceClientModel(model_id="meta-llama/Llama-3.3-70B-Instruct", provider="fireworks-ai"),
verbosity_level=1,
planning_interval=3,
name="example_agent",
descripti... | smolagents/examples/gradio_ui.py/0 | {
"file_path": "smolagents/examples/gradio_ui.py",
"repo_id": "smolagents",
"token_count": 184
} | 309 |
# Shamelessly stolen from Microsoft Autogen team: thanks to them for this great resource!
# https://github.com/microsoft/autogen/blob/gaia_multiagent_v01_march_1st/autogen/browser_utils.py
import mimetypes
import os
import pathlib
import re
import time
import uuid
from typing import Any
from urllib.parse import unquote... | smolagents/examples/open_deep_research/scripts/text_web_browser.py/0 | {
"file_path": "smolagents/examples/open_deep_research/scripts/text_web_browser.py",
"repo_id": "smolagents",
"token_count": 10239
} | 310 |
#!/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/_function_type_hints_utils.py/0 | {
"file_path": "smolagents/src/smolagents/_function_type_hints_utils.py",
"repo_id": "smolagents",
"token_count": 6241
} | 311 |
#!/usr/bin/env python
# coding=utf-8
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/L... | smolagents/src/smolagents/tools.py/0 | {
"file_path": "smolagents/src/smolagents/tools.py",
"repo_id": "smolagents",
"token_count": 25459
} | 312 |
# 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_local_python_executor.py/0 | {
"file_path": "smolagents/tests/test_local_python_executor.py",
"repo_id": "smolagents",
"token_count": 46959
} | 313 |
# Contributor Covenant Code of Conduct
## Our Pledge
We as members, contributors, and leaders pledge to make participation in our
community a harassment-free experience for everyone, regardless of age, body
size, visible or invisible disability, ethnicity, sex characteristics, gender
identity and expression, level o... | text-generation-inference/CODE_OF_CONDUCT.md/0 | {
"file_path": "text-generation-inference/CODE_OF_CONDUCT.md",
"repo_id": "text-generation-inference",
"token_count": 1206
} | 314 |
include Makefile-flash-att
include Makefile-flash-att-v2
include Makefile-vllm
include Makefile-awq
include Makefile-eetq
include Makefile-selective-scan
PROTO_PATH ?= ../proto/v3
unit-tests:
pytest -s -vv -m "not private" tests
gen-server:
# Compile protos
pip install grpcio-tools==1.62.2 mypy-protobuf==3.6.0 't... | text-generation-inference/backends/gaudi/server/Makefile/0 | {
"file_path": "text-generation-inference/backends/gaudi/server/Makefile",
"repo_id": "text-generation-inference",
"token_count": 468
} | 315 |
# Origin: https://github.com/predibase/lorax
# Path: lorax/server/lorax_server/adapters/config.py
# License: Apache License Version 2.0, January 2004
from abc import ABC, abstractmethod
from dataclasses import dataclass
from typing import Dict, Set, Tuple
import torch
from text_generation_server.adapters.weig... | text-generation-inference/backends/gaudi/server/text_generation_server/adapters/config.py/0 | {
"file_path": "text-generation-inference/backends/gaudi/server/text_generation_server/adapters/config.py",
"repo_id": "text-generation-inference",
"token_count": 275
} | 316 |
from typing import Any, Dict, List, Union
from compressed_tensors import QuantizationConfig, QuantizationStatus
from compressed_tensors.config import CompressionFormat
from compressed_tensors.quantization import (
QuantizationScheme,
QuantizationType,
find_name_or_class_matches,
)
from loguru import logger... | text-generation-inference/backends/gaudi/server/text_generation_server/layers/compressed_tensors/loader.py/0 | {
"file_path": "text-generation-inference/backends/gaudi/server/text_generation_server/layers/compressed_tensors/loader.py",
"repo_id": "text-generation-inference",
"token_count": 2625
} | 317 |
# coding=utf-8
# Copyright 2023, 2024 DeepSeek-AI 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/LI... | text-generation-inference/backends/gaudi/server/text_generation_server/layers/moe/fused_moe.py/0 | {
"file_path": "text-generation-inference/backends/gaudi/server/text_generation_server/layers/moe/fused_moe.py",
"repo_id": "text-generation-inference",
"token_count": 2009
} | 318 |
# coding=utf-8
# Copyright 2022 EleutherAI and the HuggingFace Inc. team. All rights reserved.
#
# This code is based on EleutherAI's GPT-NeoX library and the GPT-NeoX
# and OPT implementations in this library. It has been modified from its
# original forms to accommodate minor architectural differences compared
# to G... | text-generation-inference/backends/gaudi/server/text_generation_server/models/custom_modeling/flash_gpt2_modeling.py/0 | {
"file_path": "text-generation-inference/backends/gaudi/server/text_generation_server/models/custom_modeling/flash_gpt2_modeling.py",
"repo_id": "text-generation-inference",
"token_count": 6925
} | 319 |
import torch
import torch.distributed
from torch import nn
from transformers.activations import ACT2FN
from typing import Optional, List, Tuple
from text_generation_server.layers.attention import (
paged_attention,
attention,
set_block_mapping,
Seqlen,
HPUPagedAttentionMetadata,
)
from text_genera... | text-generation-inference/backends/gaudi/server/text_generation_server/models/custom_modeling/flash_santacoder_modeling.py/0 | {
"file_path": "text-generation-inference/backends/gaudi/server/text_generation_server/models/custom_modeling/flash_santacoder_modeling.py",
"repo_id": "text-generation-inference",
"token_count": 8688
} | 320 |
import os
from typing import Union
from loguru import logger
import torch
from transformers import AutoTokenizer
from peft import AutoPeftModelForCausalLM, AutoPeftModelForSeq2SeqLM
def download_and_unload_peft(model_id, revision, trust_remote_code):
torch_dtype = torch.float16
logger.info("Trying to load a... | text-generation-inference/backends/gaudi/server/text_generation_server/utils/peft.py/0 | {
"file_path": "text-generation-inference/backends/gaudi/server/text_generation_server/utils/peft.py",
"repo_id": "text-generation-inference",
"token_count": 981
} | 321 |
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
} | 322 |
#!/usr/bin/env python
import logging
import os
import sys
from text_generation_server.tgi_env import (
available_cores,
get_env_dict,
get_neuron_config_for_model,
neuron_config_to_env,
neuronxcc_version,
parse_cmdline_and_set_env,
tgi_env_vars,
)
logger = logging.getLogger(__name__)
d... | text-generation-inference/backends/neuron/tgi_entry_point.py/0 | {
"file_path": "text-generation-inference/backends/neuron/tgi_entry_point.py",
"repo_id": "text-generation-inference",
"token_count": 515
} | 323 |
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
} | 324 |
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
} | 325 |
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
} | 326 |
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
} | 327 |
# Non-core Model Serving
TGI supports various LLM architectures (see full list [here](../supported_models)). If you wish to serve a model that is not one of the supported models, TGI will fallback to the `transformers` implementation of that model. This means you will be unable to use some of the features introduced b... | text-generation-inference/docs/source/basic_tutorials/non_core_models.md/0 | {
"file_path": "text-generation-inference/docs/source/basic_tutorials/non_core_models.md",
"repo_id": "text-generation-inference",
"token_count": 472
} | 328 |
# Streaming
## What is Streaming?
Token streaming is the mode in which the server returns the tokens one by one as the model generates them. This enables showing progressive generations to the user rather than waiting for the whole generation. Streaming is an essential aspect of the end-user experience as it reduces... | text-generation-inference/docs/source/conceptual/streaming.md/0 | {
"file_path": "text-generation-inference/docs/source/conceptual/streaming.md",
"repo_id": "text-generation-inference",
"token_count": 1861
} | 329 |
# Collection of Usage Statistics
Text Generation Inference collects anonymous usage statistics to help us improve the service. The collected data is used to improve TGI and to understand what causes failures. The data is collected transparently and any sensitive information is omitted.
Usage statistics are collected... | text-generation-inference/docs/source/usage_statistics.md/0 | {
"file_path": "text-generation-inference/docs/source/usage_statistics.md",
"repo_id": "text-generation-inference",
"token_count": 966
} | 330 |
[
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [
{
"id": 17934,
"logprob": null,
"text": "Pour"
},
{
"id": 49833,
"logprob": -10.5390625,
"text": "... | text-generation-inference/integration-tests/models/__snapshots__/test_bloom_560m_sharded/test_bloom_560m_sharded_load.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_bloom_560m_sharded/test_bloom_560m_sharded_load.json",
"repo_id": "text-generation-inference",
"token_count": 7258
} | 331 |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [],
"seed": null,
"tokens": [
{
"id": 18682,
"logprob": -0.8769531,
"special": false,
"text": " Deep"
},
{
"id": 6975,
"logp... | text-generation-inference/integration-tests/models/__snapshots__/test_compressed_tensors_w8an_fp/test_compressed_tensors_w8an.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_compressed_tensors_w8an_fp/test_compressed_tensors_w8an.json",
"repo_id": "text-generation-inference",
"token_count": 869
} | 332 |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [],
"seed": null,
"tokens": [
{
"id": 185,
"logprob": -1.546875,
"special": false,
"text": "\n"
},
{
"id": 549,
"logprob": -... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_deepseek_v2/test_flash_deepseek_v2.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_deepseek_v2/test_flash_deepseek_v2.json",
"repo_id": "text-generation-inference",
"token_count": 858
} | 333 |
{
"choices": [
{
"finish_reason": "stop",
"index": 0,
"logprobs": null,
"message": {
"content": "Here's a description of what's shown in the image:\n\nThe image depicts a brown cow standing on a sandy beach. The beach has turquoise water and a distant island visible in the backgrou... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_gemma3/test_flash_gemma3_image_cow.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_gemma3/test_flash_gemma3_image_cow.json",
"repo_id": "text-generation-inference",
"token_count": 334
} | 334 |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [],
"seed": 0,
"tokens": [
{
"id": 13,
"logprob": -1.9980469,
"special": false,
"text": "."
},
{
"id": 578,
"logprob": -0.15... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_llama_exl2/test_flash_llama_exl2_all_params.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_llama_exl2/test_flash_llama_exl2_all_params.json",
"repo_id": "text-generation-inference",
"token_count": 856
} | 335 |
[
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [],
"seed": null,
"tokens": [
{
"id": 5229,
"logprob": -2.7988281,
"special": false,
"text": " failed"
},
{
... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_llama_marlin_24/test_flash_llama_marlin24_load.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_llama_marlin_24/test_flash_llama_marlin24_load.json",
"repo_id": "text-generation-inference",
"token_count": 4056
} | 336 |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [],
"seed": 0,
"tokens": [
{
"id": 13,
"logprob": 0.0,
"special": false,
"text": "\n"
},
{
"id": 23229,
"logprob": -0.182373... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_mixtral_gptq/test_flash_mixtral_gptq_all_params.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_mixtral_gptq/test_flash_mixtral_gptq_all_params.json",
"repo_id": "text-generation-inference",
"token_count": 848
} | 337 |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [],
"seed": 0,
"tokens": [
{
"id": 311,
"logprob": -1.4277344,
"special": false,
"text": " to"
},
{
"id": 279,
"logprob": -0... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_qwen2/test_flash_qwen2_all_params.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_qwen2/test_flash_qwen2_all_params.json",
"repo_id": "text-generation-inference",
"token_count": 876
} | 338 |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 60,
"prefill": [],
"seed": 0,
"tokens": [
{
"id": 2284,
"logprob": -0.31323242,
"special": false,
"text": "():"
},
{
"id": 303,
"logprob": ... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_starcoder2/test_flash_starcoder2_default_params.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_starcoder2/test_flash_starcoder2_default_params.json",
"repo_id": "text-generation-inference",
"token_count": 4512
} | 339 |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [],
"seed": 0,
"tokens": [
{
"id": 288,
"logprob": -0.2854004,
"special": false,
"text": "ing"
},
{
"id": 264,
"logprob": -0... | text-generation-inference/integration-tests/models/__snapshots__/test_idefics2/test_flash_idefics2_next_all_params.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_idefics2/test_flash_idefics2_next_all_params.json",
"repo_id": "text-generation-inference",
"token_count": 860
} | 340 |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [
{
"id": 2502,
"logprob": null,
"text": " red"
},
{
"id": 13,
"logprob": -2.734375,
"text": ","
},
{
"id": 8862... | text-generation-inference/integration-tests/models/__snapshots__/test_mamba/test_mamba_all_params.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_mamba/test_mamba_all_params.json",
"repo_id": "text-generation-inference",
"token_count": 1155
} | 341 |
{
"details": {
"best_of_sequences": null,
"finish_reason": "eos_token",
"generated_tokens": 8,
"prefill": [],
"seed": null,
"tokens": [
{
"id": 330,
"logprob": -0.107421875,
"special": false,
"text": " A"
},
{
"id": 11426,
"logp... | text-generation-inference/integration-tests/models/__snapshots__/test_smolvlm/test_flash_smolvlm_next_simple_url.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_smolvlm/test_flash_smolvlm_next_simple_url.json",
"repo_id": "text-generation-inference",
"token_count": 718
} | 342 |
{
"choices": [
{
"finish_reason": "stop",
"index": 0,
"logprobs": null,
"message": {
"content": "The image is a blank white space with no visible objects or features. It appears to be an empty or placeholder image, devoid of any content or visual elements.",
"name": null,
... | text-generation-inference/integration-tests/models/__snapshots__/test_transformers_llama4/test_flash_llama4_image_base64_rgb_jpg.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_transformers_llama4/test_flash_llama4_image_base64_rgb_jpg.json",
"repo_id": "text-generation-inference",
"token_count": 301
} | 343 |
import pytest
@pytest.fixture(scope="module")
def compressed_tensors_wna16_int_24_handle(launcher):
with launcher(
"danieldk/Llama-3.1-8B-w4a16-int-24",
num_shard=2,
quantize="compressed-tensors",
) as handle:
yield handle
@pytest.fixture(scope="module")
async def compressed_... | text-generation-inference/integration-tests/models/test_compressed_tensors_wna16_int_24.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_compressed_tensors_wna16_int_24.py",
"repo_id": "text-generation-inference",
"token_count": 1080
} | 344 |
import pytest
@pytest.fixture(scope="module")
def flash_llama_gptq_handle(launcher):
with launcher(
"astronomer/Llama-3-8B-Instruct-GPTQ-4-Bit", num_shard=2, quantize="gptq"
) as handle:
yield handle
@pytest.fixture(scope="module")
async def flash_llama_gptq(flash_llama_gptq_handle):
awa... | text-generation-inference/integration-tests/models/test_flash_llama_gptq.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_flash_llama_gptq.py",
"repo_id": "text-generation-inference",
"token_count": 769
} | 345 |
import pytest
@pytest.fixture(scope="module")
def flash_qwen2_handle(launcher):
with launcher("Qwen/Qwen1.5-0.5B") as handle:
yield handle
@pytest.fixture(scope="module")
async def flash_qwen2(flash_qwen2_handle):
await flash_qwen2_handle.health(300)
return flash_qwen2_handle.client
@pytest.ma... | text-generation-inference/integration-tests/models/test_flash_qwen2.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_flash_qwen2.py",
"repo_id": "text-generation-inference",
"token_count": 747
} | 346 |
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
} | 347 |
[tool.poetry]
name = "text-generation-inference-benchmarks"
version = "0.1.0"
description = ""
authors = ["Hugo Larcher <hugo.larcher@huggingface.co>"]
readme = "README.md"
[tool.poetry.dependencies]
python = "^3.11"
docker = "^7.1.0"
loguru = "^0.7.2"
psutil = "^6.0.0"
gputil = "^1.4.0"
pandas = "^2.2.3"
pyarrow = "^... | text-generation-inference/load_tests/pyproject.toml/0 | {
"file_path": "text-generation-inference/load_tests/pyproject.toml",
"repo_id": "text-generation-inference",
"token_count": 195
} | 348 |
use crate::infer::InferError;
use crate::{
FunctionDefinition, FunctionRef, FunctionsMap, JsonSchemaTool, Properties, Tool, ToolChoice,
};
use serde_json::{json, Map, Value};
use std::collections::HashMap;
pub(crate) struct ToolGrammar {}
impl ToolGrammar {
// find a tool by name
fn find_tool_by_name(tool... | text-generation-inference/router/src/infer/tool_grammar.rs/0 | {
"file_path": "text-generation-inference/router/src/infer/tool_grammar.rs",
"repo_id": "text-generation-inference",
"token_count": 2647
} | 349 |
flash_att_commit := ceee0de88c037ee6eda5e75c813a8648e4bcb1c9
build-flash-attention:
if [ ! -d 'flash-attention' ]; then \
pip install -U packaging ninja --no-cache-dir && \
git clone https://github.com/Narsil/flash-attention.git; \
fi
cd flash-attention && git fetch && git checkout $(flash_att_commit) && \
MA... | text-generation-inference/server/Makefile-flash-att/0 | {
"file_path": "text-generation-inference/server/Makefile-flash-att",
"repo_id": "text-generation-inference",
"token_count": 236
} | 350 |
// Adapted from turboderp exllama: https://github.com/turboderp/exllama
#ifndef _q4_matmul_cuh
#define _q4_matmul_cuh
#include <cuda_runtime.h>
#include <cuda_fp16.h>
#include <cstdint>
#include <cstdio>
#include <ATen/cuda/CUDAContext.h>
#include "q4_matrix.cuh"
#include "../tuning.h"
void q4_matmul_cuda
(
ExL... | text-generation-inference/server/exllama_kernels/exllama_kernels/cuda_func/q4_matmul.cuh/0 | {
"file_path": "text-generation-inference/server/exllama_kernels/exllama_kernels/cuda_func/q4_matmul.cuh",
"repo_id": "text-generation-inference",
"token_count": 322
} | 351 |
#include "compat.cuh"
__forceinline__ __device__ half2 dot22_8(half2(&dq)[4], const half* a_ptr, const half2 g_result)
{
half2 result = {};
const half2* a2_ptr = (const half2*)a_ptr;
#pragma unroll
for (int i = 0; i < 4; i++) result = __hfma2(dq[i], *a2_ptr++, result);
return __hadd2(result, g_resu... | text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/q_gemm_kernel_gptq.cuh/0 | {
"file_path": "text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/q_gemm_kernel_gptq.cuh",
"repo_id": "text-generation-inference",
"token_count": 4839
} | 352 |
import pytest
import torch
from text_generation_server.utils.weights import (
DefaultWeightsLoader,
Weights,
WeightsLoader,
)
from text_generation_server.layers.gptq import GPTQWeight, GPTQWeightsLoader
from text_generation_server.layers.exl2 import Exl2Weight, Exl2WeightsLoader
from text_generation_server.... | text-generation-inference/server/tests/utils/test_weights.py/0 | {
"file_path": "text-generation-inference/server/tests/utils/test_weights.py",
"repo_id": "text-generation-inference",
"token_count": 17962
} | 353 |
from typing import Tuple
from dataclasses import dataclass, field
from loguru import logger
import torch
from text_generation_server.layers.fp8 import fp8_quantize
from text_generation_server.models.globals import ATTENTION, BLOCK_SIZE
from text_generation_server.utils.import_utils import SYSTEM
from text_generation_... | text-generation-inference/server/text_generation_server/layers/attention/kv_cache.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/layers/attention/kv_cache.py",
"repo_id": "text-generation-inference",
"token_count": 5908
} | 354 |
from dataclasses import dataclass
import os
from typing import Optional, Tuple, Type, Union, List
import torch
from loguru import logger
from text_generation_server.utils.import_utils import SYSTEM
from text_generation_server.utils.kernels import load_kernel
from text_generation_server.utils.weights import (
Weig... | text-generation-inference/server/text_generation_server/layers/fp8.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/layers/fp8.py",
"repo_id": "text-generation-inference",
"token_count": 10546
} | 355 |
import functools
from typing import List, Tuple
import numpy
import torch
from text_generation_server.utils.import_utils import SYSTEM
from text_generation_server.utils.kernels import load_kernel
if SYSTEM == "cuda":
quantization = load_kernel(
module="quantization", repo_id="kernels-community/quantizatio... | text-generation-inference/server/text_generation_server/layers/marlin/util.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/layers/marlin/util.py",
"repo_id": "text-generation-inference",
"token_count": 1826
} | 356 |
from typing import Optional, Tuple
import torch
from torch import nn
from transformers.activations import ACT2FN
from transformers.modeling_attn_mask_utils import (
_create_4d_causal_attention_mask,
_prepare_4d_attention_mask,
)
from transformers.modeling_outputs import (
BaseModelOutputWithPooling,
)
fro... | text-generation-inference/server/text_generation_server/models/custom_modeling/clip.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/models/custom_modeling/clip.py",
"repo_id": "text-generation-inference",
"token_count": 13765
} | 357 |
# coding=utf-8
# Copyright 2024 Microsoft 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/LICENSE-2.... | text-generation-inference/server/text_generation_server/models/custom_modeling/flash_phi_moe_modeling.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/models/custom_modeling/flash_phi_moe_modeling.py",
"repo_id": "text-generation-inference",
"token_count": 5177
} | 358 |
# coding=utf-8
# Copyright 2021 The OpenAI Team Authors and 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/L... | text-generation-inference/server/text_generation_server/models/custom_modeling/idefics_vision.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/models/custom_modeling/idefics_vision.py",
"repo_id": "text-generation-inference",
"token_count": 9625
} | 359 |
from io import BytesIO
from PIL import Image
import torch
import time
from dataclasses import dataclass
from opentelemetry import trace
from transformers import (
AutoConfig,
AutoProcessor,
AutoTokenizer,
PreTrainedTokenizerBase,
ProcessorMixin,
)
from typing import Optional, Tuple, List, Type, Dic... | text-generation-inference/server/text_generation_server/models/idefics_causal_lm.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/models/idefics_causal_lm.py",
"repo_id": "text-generation-inference",
"token_count": 17112
} | 360 |
import datetime
import torch
import os
from loguru import logger
from pathlib import Path
from safetensors.torch import save_file, load_file, _find_shared_tensors, _is_complete
from typing import List, Dict
from collections import defaultdict
def _remove_duplicate_names(
state_dict: Dict[str, torch.Tensor],
... | text-generation-inference/server/text_generation_server/utils/convert.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/utils/convert.py",
"repo_id": "text-generation-inference",
"token_count": 1775
} | 361 |
import torch
from abc import ABC, abstractmethod
from contextlib import contextmanager
from pathlib import Path
from typing import Dict, List, Optional, Union, Type
from safetensors import safe_open
from dataclasses import dataclass
from text_generation_server.utils.import_utils import SYSTEM
class WeightsLoader(AB... | text-generation-inference/server/text_generation_server/utils/weights.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/utils/weights.py",
"repo_id": "text-generation-inference",
"token_count": 6743
} | 362 |
MIT License
Copyright (c) 2020 N-API for Rust
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, merge, publish, di... | tokenizers/bindings/node/LICENSE/0 | {
"file_path": "tokenizers/bindings/node/LICENSE",
"repo_id": "tokenizers",
"token_count": 276
} | 363 |
/* eslint-disable @typescript-eslint/no-explicit-any */
import { bertProcessing, byteLevelProcessing, robertaProcessing, sequenceProcessing, templateProcessing } from '../../'
describe('bertProcessing', () => {
it('instantiates correctly with only two parameters', () => {
const processor = bertProcessing(['sep'... | tokenizers/bindings/node/lib/bindings/post-processors.test.ts/0 | {
"file_path": "tokenizers/bindings/node/lib/bindings/post-processors.test.ts",
"repo_id": "tokenizers",
"token_count": 1022
} | 364 |
# `tokenizers-linux-arm64-gnu`
This is the **aarch64-unknown-linux-gnu** binary for `tokenizers`
| tokenizers/bindings/node/npm/linux-arm64-gnu/README.md/0 | {
"file_path": "tokenizers/bindings/node/npm/linux-arm64-gnu/README.md",
"repo_id": "tokenizers",
"token_count": 35
} | 365 |
use serde::de::Deserializer;
use serde::ser::Serializer;
use serde::{Deserialize, Serialize};
use std::sync::{Arc, RwLock};
pub fn serialize<S, T>(val: &Option<Arc<RwLock<T>>>, s: S) -> Result<S::Ok, S::Error>
where
S: Serializer,
T: Serialize,
{
T::serialize(&*(val.clone().unwrap()).read().unwrap(), s)
}
pub f... | tokenizers/bindings/node/src/arc_rwlock_serde.rs/0 | {
"file_path": "tokenizers/bindings/node/src/arc_rwlock_serde.rs",
"repo_id": "tokenizers",
"token_count": 220
} | 366 |
# This file is generated by running "yarn install" inside your project.
# Manual changes might be lost - proceed with caution!
__metadata:
version: 6
cacheKey: 8
"@aashutoshrathi/word-wrap@npm:^1.2.3":
version: 1.2.6
resolution: "@aashutoshrathi/word-wrap@npm:1.2.6"
checksum: ada901b9e7c680d190f1d012c84217c... | tokenizers/bindings/node/yarn.lock/0 | {
"file_path": "tokenizers/bindings/node/yarn.lock",
"repo_id": "tokenizers",
"token_count": 125916
} | 367 |
from enum import Enum
from typing import List, Tuple, Union
Offsets = Tuple[int, int]
TextInputSequence = str
"""A :obj:`str` that represents an input sequence """
PreTokenizedInputSequence = Union[List[str], Tuple[str]]
"""A pre-tokenized input sequence. Can be one of:
- A :obj:`List` of :obj:`str`
- A :o... | tokenizers/bindings/python/py_src/tokenizers/__init__.py/0 | {
"file_path": "tokenizers/bindings/python/py_src/tokenizers/__init__.py",
"repo_id": "tokenizers",
"token_count": 984
} | 368 |
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