text stringlengths 5 409k | id stringlengths 14 178 | metadata dict | __index_level_0__ int64 0 572 |
|---|---|---|---|
.PHONY: test precommit common_tests slow_tests test_examples tests_gpu
check_dirs := examples tests trl
ACCELERATE_CONFIG_PATH = `pwd`/examples/accelerate_configs
COMMAND_FILES_PATH = `pwd`/commands
test:
python -m pytest -n auto --dist=loadfile -s -v --reruns 5 --reruns-delay 1 --only-rerun '(OSError|Timeout|HTTPE... | trl/Makefile/0 | {
"file_path": "trl/Makefile",
"repo_id": "trl",
"token_count": 459
} | 528 |
# Dataset formats and types
This guide provides an overview of the dataset formats and types supported by each trainer in TRL.
## Overview of the dataset formats and types
- The *format* of a dataset refers to how the data is structured, typically categorized as either *standard* or *conversational*.
- The *type* is... | trl/docs/source/dataset_formats.md/0 | {
"file_path": "trl/docs/source/dataset_formats.md",
"repo_id": "trl",
"token_count": 16437
} | 529 |
# Logging
As reinforcement learning algorithms are historically challenging to debug, it's important to pay careful attention to logging.
By default, the TRL [`PPOTrainer`] saves a lot of relevant information to wandb or tensorboard.
Upon initialization, pass one of these two options to the [`PPOConfig`]:
```
traini... | trl/docs/source/logging.md/0 | {
"file_path": "trl/docs/source/logging.md",
"repo_id": "trl",
"token_count": 1944
} | 530 |
# Speeding Up Training
<Tip warning={true}>
Section under construction. Feel free to contribute!
</Tip>
## vLLM for fast generation in online methods
Online methods such as GRPO or Online DPO require the model to generate completions, which is often a slow process and can significantly impact training time.
To spe... | trl/docs/source/speeding_up_training.md/0 | {
"file_path": "trl/docs/source/speeding_up_training.md",
"repo_id": "trl",
"token_count": 699
} | 531 |
# Copyright 2025 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | trl/examples/datasets/lm-human-preferences-sentiment.py/0 | {
"file_path": "trl/examples/datasets/lm-human-preferences-sentiment.py",
"repo_id": "trl",
"token_count": 1586
} | 532 |
# Copyright 2025 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | trl/examples/research_projects/stack_llama/scripts/rl_training.py/0 | {
"file_path": "trl/examples/research_projects/stack_llama/scripts/rl_training.py",
"repo_id": "trl",
"token_count": 3755
} | 533 |
# Copyright 2025 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | trl/examples/scripts/sft_vlm.py/0 | {
"file_path": "trl/examples/scripts/sft_vlm.py",
"repo_id": "trl",
"token_count": 1914
} | 534 |
# Copyright 2025 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | trl/tests/test_gkd_trainer.py/0 | {
"file_path": "trl/tests/test_gkd_trainer.py",
"repo_id": "trl",
"token_count": 5292
} | 535 |
# Copyright 2025 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | trl/tests/test_sft_trainer.py/0 | {
"file_path": "trl/tests/test_sft_trainer.py",
"repo_id": "trl",
"token_count": 29553
} | 536 |
# Copyright 2025 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | trl/trl/import_utils.py/0 | {
"file_path": "trl/trl/import_utils.py",
"repo_id": "trl",
"token_count": 1598
} | 537 |
# Copyright 2025 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | trl/trl/scripts/utils.py/0 | {
"file_path": "trl/trl/scripts/utils.py",
"repo_id": "trl",
"token_count": 3753
} | 538 |
# Copyright 2025 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | trl/trl/trainer/grpo_config.py/0 | {
"file_path": "trl/trl/trainer/grpo_config.py",
"repo_id": "trl",
"token_count": 5235
} | 539 |
# Copyright 2025 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | trl/trl/trainer/prm_trainer.py/0 | {
"file_path": "trl/trl/trainer/prm_trainer.py",
"repo_id": "trl",
"token_count": 7231
} | 540 |
<!---
Copyright 2022 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 ... | accelerate/CONTRIBUTING.md/0 | {
"file_path": "accelerate/CONTRIBUTING.md",
"repo_id": "accelerate",
"token_count": 2693
} | 0 |
# 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
#
# Unless required by appl... | accelerate/benchmarks/fp8/torchao/distrib_deepspeed.py/0 | {
"file_path": "accelerate/benchmarks/fp8/torchao/distrib_deepspeed.py",
"repo_id": "accelerate",
"token_count": 3238
} | 1 |
<!--Copyright 2022 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... | accelerate/docs/source/concept_guides/performance.md/0 | {
"file_path": "accelerate/docs/source/concept_guides/performance.md",
"repo_id": "accelerate",
"token_count": 1476
} | 2 |
<!--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... | accelerate/docs/source/usage_guides/local_sgd.md/0 | {
"file_path": "accelerate/docs/source/usage_guides/local_sgd.md",
"repo_id": "accelerate",
"token_count": 1475
} | 3 |
#!/usr/bin/env python
# Copyright 2022 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
#
# U... | accelerate/examples/by_feature/deepspeed_with_config_support.py/0 | {
"file_path": "accelerate/examples/by_feature/deepspeed_with_config_support.py",
"repo_id": "accelerate",
"token_count": 12478
} | 4 |
# This config template simply setups up the TransformersEngine config (and a config for a single GPU),
# this can interop with the other configs in this folder
distributed_type: "NO"
mixed_precision: "fp8"
# Then we specify the fp8 configuration:
fp8_config:
backend: TE # Can be TE | MS-AMP
# The following are TE s... | accelerate/examples/config_yaml_templates/fp8.yaml/0 | {
"file_path": "accelerate/examples/config_yaml_templates/fp8.yaml",
"repo_id": "accelerate",
"token_count": 245
} | 5 |
# 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
#
# Unless required by appl... | accelerate/examples/inference/distributed/phi2.py/0 | {
"file_path": "accelerate/examples/inference/distributed/phi2.py",
"repo_id": "accelerate",
"token_count": 1161
} | 6 |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate/manim_animations/big_model_inference/stage_1.py/0 | {
"file_path": "accelerate/manim_animations/big_model_inference/stage_1.py",
"repo_id": "accelerate",
"token_count": 1904
} | 7 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate/src/accelerate/accelerator.py/0 | {
"file_path": "accelerate/src/accelerate/accelerator.py",
"repo_id": "accelerate",
"token_count": 73491
} | 8 |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate/src/accelerate/memory_utils.py/0 | {
"file_path": "accelerate/src/accelerate/memory_utils.py",
"repo_id": "accelerate",
"token_count": 237
} | 9 |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate/src/accelerate/test_utils/scripts/test_ddp_comm_hook.py/0 | {
"file_path": "accelerate/src/accelerate/test_utils/scripts/test_ddp_comm_hook.py",
"repo_id": "accelerate",
"token_count": 1232
} | 10 |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate/src/accelerate/utils/environment.py/0 | {
"file_path": "accelerate/src/accelerate/utils/environment.py",
"repo_id": "accelerate",
"token_count": 5668
} | 11 |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate/tests/test_offload.py/0 | {
"file_path": "accelerate/tests/test_offload.py",
"repo_id": "accelerate",
"token_count": 1981
} | 12 |
# When will the next units be published?
Here's the publication schedule:
<img src="https://huggingface.co/datasets/agents-course/course-images/resolve/main/en/communication/next-units.jpg" alt="Next Units" width="100%"/>
Don't forget to <a href="https://bit.ly/hf-learn-agents">sign up for the course</a>! By signing... | agents-course/units/en/communication/next-units.mdx/0 | {
"file_path": "agents-course/units/en/communication/next-units.mdx",
"repo_id": "agents-course",
"token_count": 138
} | 13 |
# What are Tools?
<img src="https://huggingface.co/datasets/agents-course/course-images/resolve/main/en/unit1/whiteboard-check-2.jpg" alt="Unit 1 planning"/>
One crucial aspect of AI Agents is their ability to take **actions**. As we saw, this happens through the use of **Tools**.
In this section, we’ll learn what T... | agents-course/units/en/unit1/tools.mdx/0 | {
"file_path": "agents-course/units/en/unit1/tools.mdx",
"repo_id": "agents-course",
"token_count": 4085
} | 14 |
# Porting a custom kernel
| candle/candle-book/src/cuda/porting.md/0 | {
"file_path": "candle/candle-book/src/cuda/porting.md",
"repo_id": "candle",
"token_count": 7
} | 15 |
# Simplified
## How its works
This program implements a neural network to predict the winner of the second round of elections based on the results of the first round.
Basic moments:
1. A multilayer perceptron with two hidden layers is used. The first hidden layer has 4 neurons, the second has 2 neurons.
2. The inpu... | candle/candle-book/src/training/simplified.md/0 | {
"file_path": "candle/candle-book/src/training/simplified.md",
"repo_id": "candle",
"token_count": 530
} | 16 |
#[cfg(feature = "accelerate")]
extern crate accelerate_src;
#[cfg(feature = "mkl")]
extern crate intel_mkl_src;
use anyhow::Result;
use candle_core::{Device, Tensor};
fn main() -> Result<()> {
let device = Device::new_cuda(0)?;
let x = Tensor::randn(0f32, 1.0, (8 * 4096, 8 * 4096), &device)?
.to_dtyp... | candle/candle-core/examples/cuda_basics.rs/0 | {
"file_path": "candle/candle-core/examples/cuda_basics.rs",
"repo_id": "candle",
"token_count": 477
} | 17 |
use crate::WithDType;
use cudarc;
use cudarc::cudnn::safe::{ConvForward, Cudnn};
use cudarc::driver::{CudaSlice, CudaView, DeviceRepr, ValidAsZeroBits};
use std::cell::RefCell;
use std::collections::HashMap;
use std::sync::Arc;
// The cudnn handles are stored per thread here rather than on the CudaDevice as they are n... | candle/candle-core/src/cuda_backend/cudnn.rs/0 | {
"file_path": "candle/candle-core/src/cuda_backend/cudnn.rs",
"repo_id": "candle",
"token_count": 2242
} | 18 |
//! Implementation of Backend traits for Metal
//!
use crate::backend::{BackendDevice, BackendStorage};
use crate::conv::{ParamsConv1D, ParamsConv2D, ParamsConvTranspose1D, ParamsConvTranspose2D};
use crate::op::{BinaryOpT, CmpOp, ReduceOp, UnaryOpT};
use crate::{CpuStorage, CpuStorageRef, DType, Layout, Result, Shape}... | candle/candle-core/src/metal_backend/mod.rs/0 | {
"file_path": "candle/candle-core/src/metal_backend/mod.rs",
"repo_id": "candle",
"token_count": 51267
} | 19 |
use crate::Result;
pub(super) fn nearest_int(v: f32) -> i32 {
v.round() as i32
}
/// Validates that the input and output are the right size and returns an iterator which maps each
/// input region `xs` to its corresponding output block in `ys`. Each output region is guaranteed
/// to be `T::BLCK_SIZE` long.
pub(s... | candle/candle-core/src/quantized/utils.rs/0 | {
"file_path": "candle/candle-core/src/quantized/utils.rs",
"repo_id": "candle",
"token_count": 5775
} | 20 |
[package]
name = "candle-datasets"
version.workspace = true
edition.workspace = true
description.workspace = true
repository.workspace = true
keywords.workspace = true
categories.workspace = true
license.workspace = true
readme = "README.md"
[dependencies]
byteorder = { workspace = true }
candle = { workspace = true }... | candle/candle-datasets/Cargo.toml/0 | {
"file_path": "candle/candle-datasets/Cargo.toml",
"repo_id": "candle",
"token_count": 201
} | 21 |
//! BEiT: BERT Pre-Training of Image Transformers
//! https://github.com/microsoft/unilm/tree/master/beit
#[cfg(feature = "mkl")]
extern crate intel_mkl_src;
#[cfg(feature = "accelerate")]
extern crate accelerate_src;
use clap::Parser;
use candle::{DType, Device, IndexOp, Result, Tensor, D};
use candle_nn::{Module,... | candle/candle-examples/examples/beit/main.rs/0 | {
"file_path": "candle/candle-examples/examples/beit/main.rs",
"repo_id": "candle",
"token_count": 1178
} | 22 |
# candle-convnext
[A ConvNet for the 2020s](https://arxiv.org/abs/2201.03545) and
[ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders](https://arxiv.org/abs/2301.00808).
This candle implementation uses a pre-trained ConvNeXt network for inference. The
classification head has been trained on the I... | candle/candle-examples/examples/convnext/README.md/0 | {
"file_path": "candle/candle-examples/examples/convnext/README.md",
"repo_id": "candle",
"token_count": 293
} | 23 |
# candle-flux: image generation with latent rectified flow transformers
Flux is a 12B rectified flow transformer capable of generating images from text
descriptions,
[huggingface](https://huggingface.co/black-forest-labs/FLUX.1-schnell),
[github](https://github... | candle/candle-examples/examples/flux/README.md/0 | {
"file_path": "candle/candle-examples/examples/flux/README.md",
"repo_id": "candle",
"token_count": 216
} | 24 |
# candle-jina-bert
Jina-Bert is a general large language model with a context size of 8192, [model
card](https://huggingface.co/jinaai/jina-embeddings-v2-base-en). In this example
it can be used for two different tasks:
- Compute sentence embeddings for a prompt.
- Compute similarities between a set of sentences.
##... | candle/candle-examples/examples/jina-bert/README.md/0 | {
"file_path": "candle/candle-examples/examples/jina-bert/README.md",
"repo_id": "candle",
"token_count": 663
} | 25 |
#[cfg(feature = "mkl")]
extern crate intel_mkl_src;
#[cfg(feature = "accelerate")]
extern crate accelerate_src;
use anyhow::{Error as E, Result};
use clap::{Parser, ValueEnum};
use candle_transformers::models::mamba::{Config, Model, State};
use candle::{DType, Device, Tensor};
use candle_examples::token_output_stre... | candle/candle-examples/examples/mamba/main.rs/0 | {
"file_path": "candle/candle-examples/examples/mamba/main.rs",
"repo_id": "candle",
"token_count": 4425
} | 26 |
# candle-mobilenetv4
[MobileNetV4 - Universal Models for the Mobile Ecosystem](https://arxiv.org/abs/2404.10518)
This candle implementation uses pre-trained MobileNetV4 models from timm for inference.
The classification head has been trained on the ImageNet dataset and returns the probabilities for the top-5 classes.
... | candle/candle-examples/examples/mobilenetv4/README.md/0 | {
"file_path": "candle/candle-examples/examples/mobilenetv4/README.md",
"repo_id": "candle",
"token_count": 248
} | 27 |
use anyhow::Result;
use candle::{Device, Tensor};
use clap::{Parser, Subcommand};
#[derive(Subcommand, Debug, Clone)]
enum Command {
Print {
#[arg(long)]
file: String,
},
SimpleEval {
#[arg(long)]
file: String,
},
}
#[derive(Parser, Debug)]
#[command(author, version, a... | candle/candle-examples/examples/onnx_basics.rs/0 | {
"file_path": "candle/candle-examples/examples/onnx_basics.rs",
"repo_id": "candle",
"token_count": 2016
} | 28 |
# candle-repvgg
[RepVGG: Making VGG-style ConvNets Great Again](https://arxiv.org/abs/2101.03697).
This candle implementation uses a pre-trained RepVGG network for inference. The
classification head has been trained on the ImageNet dataset and returns the
probabilities for the top-5 classes.
## Running an example
`... | candle/candle-examples/examples/repvgg/README.md/0 | {
"file_path": "candle/candle-examples/examples/repvgg/README.md",
"repo_id": "candle",
"token_count": 254
} | 29 |
#[cfg(feature = "mkl")]
extern crate intel_mkl_src;
#[cfg(feature = "accelerate")]
extern crate accelerate_src;
use anyhow::Error as E;
use clap::Parser;
use candle::{DType, Device, Tensor};
use candle_nn::{ops::softmax, VarBuilder};
use candle_transformers::models::siglip;
use tokenizers::Tokenizer;
#[derive(Pars... | candle/candle-examples/examples/siglip/main.rs/0 | {
"file_path": "candle/candle-examples/examples/siglip/main.rs",
"repo_id": "candle",
"token_count": 2315
} | 30 |
# candle-whisper: speech recognition
An implementation of [OpenAI Whisper](https://github.com/openai/whisper) using
candle. Whisper is a general purpose speech recognition model, it can be used to
convert audio files (in the `.wav` format) to text. Supported features include
language detection as well as multilingual ... | candle/candle-examples/examples/whisper/README.md/0 | {
"file_path": "candle/candle-examples/examples/whisper/README.md",
"repo_id": "candle",
"token_count": 627
} | 31 |
[net]
# Testing
batch=1
subdivisions=1
# Training
# batch=64
# subdivisions=16
width= 416
height = 416
channels=3
momentum=0.9
decay=0.0005
angle=0
saturation = 1.5
exposure = 1.5
hue=.1
learning_rate=0.001
burn_in=1000
max_batches = 500200
policy=steps
steps=400000,450000
scales=.1,.1
[convolutional]
batch_normaliz... | candle/candle-examples/examples/yolo-v3/yolo-v3.cfg/0 | {
"file_path": "candle/candle-examples/examples/yolo-v3/yolo-v3.cfg",
"repo_id": "candle",
"token_count": 3586
} | 32 |
[package]
name = "candle-flash-attn"
version = "0.8.3"
edition = "2021"
description = "Flash attention layer for the candle ML framework."
repository = "https://github.com/huggingface/candle"
keywords = ["blas", "tensor", "machine-learning"]
categories = ["science"]
license = "MIT OR Apache-2.0"
readme = "README.md"
... | candle/candle-flash-attn/Cargo.toml/0 | {
"file_path": "candle/candle-flash-attn/Cargo.toml",
"repo_id": "candle",
"token_count": 266
} | 33 |
/******************************************************************************
* Copyright (c) 2024, Tri Dao.
******************************************************************************/
#pragma once
#include <cute/tensor.hpp>
namespace flash {
using namespace cute;
template <typename Engine, typename Layout... | candle/candle-flash-attn/kernels/mask.h/0 | {
"file_path": "candle/candle-flash-attn/kernels/mask.h",
"repo_id": "candle",
"token_count": 6255
} | 34 |
#include "cuda_fp16.h"
#include "cuda_bf16.h"
// Table showing which features are supported on which compute capability
// https://docs.nvidia.com/cuda/cuda-c-programming-guide/#features-and-technical-specifications
// FIXME: the minimum compute capabilities are just guesses since the table is not specific enough
#i... | candle/candle-kernels/src/compatibility.cuh/0 | {
"file_path": "candle/candle-kernels/src/compatibility.cuh",
"repo_id": "candle",
"token_count": 2734
} | 35 |
#include <metal_stdlib>
METAL_FUNC uint get_strided_index(
uint idx,
constant size_t &num_dims,
constant size_t *dims,
constant size_t *strides
) {
uint strided_i = 0;
for (uint d = 0; d < num_dims; d++) {
uint dim_idx = num_dims - 1 - d;
strided_i += (idx % dims[dim_idx]) * str... | candle/candle-metal-kernels/src/cast.metal/0 | {
"file_path": "candle/candle-metal-kernels/src/cast.metal",
"repo_id": "candle",
"token_count": 2045
} | 36 |
#include <metal_stdlib>
#include <metal_math>
#
using namespace metal;
METAL_FUNC uint get_strided_index(
uint idx,
constant size_t &num_dims,
constant size_t *dims,
constant size_t *strides
) {
uint strided_i = 0;
for (uint d = 0; d < num_dims; d++) {
uint dim_idx = num_dims - 1 - d;
... | candle/candle-metal-kernels/src/unary.metal/0 | {
"file_path": "candle/candle-metal-kernels/src/unary.metal",
"repo_id": "candle",
"token_count": 2665
} | 37 |
//! Activation Functions
//!
use candle::{Result, Tensor};
#[derive(Debug, Clone, Copy, PartialEq, serde::Deserialize, serde::Serialize, Default)]
#[serde(rename_all = "lowercase")]
pub enum Activation {
#[default]
#[serde(alias = "gelu")]
Gelu,
#[serde(alias = "gelu_new")]
NewGelu,
Relu,
R... | candle/candle-nn/src/activation.rs/0 | {
"file_path": "candle/candle-nn/src/activation.rs",
"repo_id": "candle",
"token_count": 1665
} | 38 |
//! Rotary Embeddings
//!
use candle::{CpuStorage, Layout, Result, Shape, Tensor, D};
use rayon::prelude::*;
/// Interleaved variant of rotary embeddings.
/// The x0 and x1 value are interleaved on the n_embd (= head_dim) dimension.
/// The resulting y0 and y1 are also interleaved with:
/// y0 = x0*cos - x1*sin
/// ... | candle/candle-nn/src/rotary_emb.rs/0 | {
"file_path": "candle/candle-nn/src/rotary_emb.rs",
"repo_id": "candle",
"token_count": 15521
} | 39 |
use std::io::Result;
fn main() -> Result<()> {
prost_build::compile_protos(&["src/onnx.proto3"], &["src/"])?;
Ok(())
}
| candle/candle-onnx/build.rs/0 | {
"file_path": "candle/candle-onnx/build.rs",
"repo_id": "candle",
"token_count": 60
} | 40 |
from dataclasses import dataclass
from typing import Optional
from candle.nn import Module, Embedding, LayerNorm, Linear, ModuleList
from candle import Tensor
import candle
import candle.functional as F
from typing import Tuple, Optional
@dataclass
class Config:
vocab_size: int = 30522
hidden_size: int = 768
... | candle/candle-pyo3/py_src/candle/models/bert.py/0 | {
"file_path": "candle/candle-pyo3/py_src/candle/models/bert.py",
"repo_id": "candle",
"token_count": 3528
} | 41 |
# This example shows how the candle Python api can be used to replicate llama.cpp.
import sys
from typing import Dict, Tuple, Any
import candle
from candle.models.llama import QuantizedLlama
from candle import utils
MAX_SEQ_LEN = 4096
def gguf_rename(tensor_name: str):
if tensor_name == "token_embd.weight":
... | candle/candle-pyo3/quant-llama.py/0 | {
"file_path": "candle/candle-pyo3/quant-llama.py",
"repo_id": "candle",
"token_count": 1318
} | 42 |
# candle-transformers
| candle/candle-transformers/README.md/0 | {
"file_path": "candle/candle-transformers/README.md",
"repo_id": "candle",
"token_count": 6
} | 43 |
//! # FastViT inference implementation based on timm
//!
//! ## Description
//! See ["FastViT: A Fast Hybrid Vision Transformer using Structural Reparameterization"](https://arxiv.org/pdf/2303.14189)
//!
//! Implementation based on [timm model](https://github.com/huggingface/pytorch-image-models/blob/main/timm/models/f... | candle/candle-transformers/src/models/fastvit.rs/0 | {
"file_path": "candle/candle-transformers/src/models/fastvit.rs",
"repo_id": "candle",
"token_count": 8020
} | 44 |
use std::collections::HashMap;
use crate::models::{
clip::{text_model::Activation, vision_model::ClipVisionConfig},
llama::{Config, LlamaEosToks},
};
use serde::{Deserialize, Serialize};
// original config from liuhaotian/llava
#[derive(Serialize, Deserialize, Debug, Clone)]
pub struct LLaVAConfig {
pub a... | candle/candle-transformers/src/models/llava/config.rs/0 | {
"file_path": "candle/candle-transformers/src/models/llava/config.rs",
"repo_id": "candle",
"token_count": 3948
} | 45 |
use candle::{bail, DType, Module, Result, Tensor};
use candle_nn as nn;
pub struct PatchEmbedder {
proj: nn::Conv2d,
}
impl PatchEmbedder {
pub fn new(
patch_size: usize,
in_channels: usize,
embed_dim: usize,
vb: nn::VarBuilder,
) -> Result<Self> {
let proj = nn::co... | candle/candle-transformers/src/models/mmdit/embedding.rs/0 | {
"file_path": "candle/candle-transformers/src/models/mmdit/embedding.rs",
"repo_id": "candle",
"token_count": 2837
} | 46 |
//! Text encoder as used in most OpenCLIP pretrained models
//! https://github.com/mlfoundations/open_clip
use candle::{DType, IndexOp, Result, Tensor, D};
use candle_nn::{
embedding, layer_norm, linear, ops::softmax_last_dim, Embedding, LayerNorm, Linear, Module,
VarBuilder,
};
#[derive(Debug, Clone)]
pub st... | candle/candle-transformers/src/models/openclip/text_model.rs/0 | {
"file_path": "candle/candle-transformers/src/models/openclip/text_model.rs",
"repo_id": "candle",
"token_count": 3955
} | 47 |
//! Implementation of a quantized Moondream vision language model.
//!
//! Moondream is a lightweight vision-language model for image understanding and generation.
//! This module provides a quantized version for reduced memory usage and faster inference.
//!
//! Key features:
//! - ViT-based vision encoder
//! - Phi-2... | candle/candle-transformers/src/models/quantized_moondream.rs/0 | {
"file_path": "candle/candle-transformers/src/models/quantized_moondream.rs",
"repo_id": "candle",
"token_count": 3810
} | 48 |
//! RWKV v6 model implementation.
//!
//! The [RWKV model](https://wiki.rwkv.com/) is a recurrent neural network model
//! with performance on par with transformer architectures. Several variants are
//! available, candle implements the v5 and v6 versions and can be used with
//! Eagle 7B([blog post](https://blog.rwkv.... | candle/candle-transformers/src/models/rwkv_v6.rs/0 | {
"file_path": "candle/candle-transformers/src/models/rwkv_v6.rs",
"repo_id": "candle",
"token_count": 6204
} | 49 |
//! Stable Diffusion
//!
//! Stable Diffusion is a latent text-to-image diffusion model capable of
//! generating photo-realistic images given any text input.
//!
//! - 💻 [Original Repository](https://github.com/CompVis/stable-diffusion)
//! - 🤗 [Hugging Face](https://huggingface.co/runwayml/stable-diffusion-v1-5)
//... | candle/candle-transformers/src/models/stable_diffusion/mod.rs/0 | {
"file_path": "candle/candle-transformers/src/models/stable_diffusion/mod.rs",
"repo_id": "candle",
"token_count": 8553
} | 50 |
//! Whisper Model Implementation
//!
//! Whisper is an automatic speech recognition (ASR) system trained on large amounts
//! of multilingual and multitask supervised data collected from the web. It can be used to
//! convert audio files (in the `.wav` format) to text. Supported features include
//! language detection ... | candle/candle-transformers/src/models/whisper/mod.rs/0 | {
"file_path": "candle/candle-transformers/src/models/whisper/mod.rs",
"repo_id": "candle",
"token_count": 1018
} | 51 |
//! Utilities for quanitized network layers
//!
//! This module contains various implementations of standard neural network layers, modules and
//! utilities including embedding, linear layers, and various normalization techniques.
//! Most implementations provide quantized weights support.
use crate::models::with_tra... | candle/candle-transformers/src/quantized_nn.rs/0 | {
"file_path": "candle/candle-transformers/src/quantized_nn.rs",
"repo_id": "candle",
"token_count": 1681
} | 52 |
use candle::{DType, Device, IndexOp, Result, Tensor, D};
use candle_nn::{
embedding, linear_no_bias as linear, rms_norm, Embedding, Linear, Module, RmsNorm, VarBuilder,
};
use std::collections::HashMap;
use std::sync::{Arc, Mutex};
#[derive(Debug, Clone)]
pub struct Config {
pub dim: usize, // transform... | candle/candle-wasm-examples/llama2-c/src/model.rs/0 | {
"file_path": "candle/candle-wasm-examples/llama2-c/src/model.rs",
"repo_id": "candle",
"token_count": 5272
} | 53 |
//load the candle Whisper decoder wasm module
import init, { Decoder } from "./build/m.js";
async function fetchArrayBuffer(url) {
const cacheName = "whisper-candle-cache";
const cache = await caches.open(cacheName);
const cachedResponse = await cache.match(url);
if (cachedResponse) {
const data = await ca... | candle/candle-wasm-examples/whisper/whisperWorker.js/0 | {
"file_path": "candle/candle-wasm-examples/whisper/whisperWorker.js",
"repo_id": "candle",
"token_count": 1215
} | 54 |
Run the tests with:
```bash
RUST_LOG=wasm_bindgen_test_runner wasm-pack test --chrome --headless
```
Or:
```bash
wasm-pack test --chrome
```
If you get an "invalid session id" failure in headless mode, check that logs and
it may well be that your ChromeDriver is not at the same version as your
browser.
| candle/candle-wasm-tests/README.md/0 | {
"file_path": "candle/candle-wasm-tests/README.md",
"repo_id": "candle",
"token_count": 98
} | 55 |
import json
import os
import tempfile
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features import Array2D
from utils import generate_examples, get_duration
SHAPE_TEST_1 = (30, 487)
SHAPE_TEST_2 = (36, 1024)
SPEED_TEST_SHAPE = (100, 100)
SPEED_TEST_N_EXAMPLES = 100
DEFAULT_FEATURES = ... | datasets/benchmarks/benchmark_array_xd.py/0 | {
"file_path": "datasets/benchmarks/benchmark_array_xd.py",
"repo_id": "datasets",
"token_count": 2176
} | 56 |
- sections:
- local: index
title: 🤗 Datasets
- local: quickstart
title: Quickstart
- local: installation
title: Installation
title: Get started
- sections:
- local: tutorial
title: Overview
- local: load_hub
title: Load a dataset from the Hub
- local: access
title: Know your data... | datasets/docs/source/_toctree.yml/0 | {
"file_path": "datasets/docs/source/_toctree.yml",
"repo_id": "datasets",
"token_count": 1315
} | 57 |
# Depth estimation
Depth estimation datasets are used to train a model to approximate the relative distance of every pixel in an
image from the camera, also known as depth. The applications enabled by these datasets primarily lie in areas like visual machine
perception and perception in robotics. Example applications ... | datasets/docs/source/depth_estimation.mdx/0 | {
"file_path": "datasets/docs/source/depth_estimation.mdx",
"repo_id": "datasets",
"token_count": 2848
} | 58 |
# Object detection
Object detection models identify something in an image, and object detection datasets are used for applications such as autonomous driving and detecting natural hazards like wildfire. This guide will show you how to apply transformations to an object detection dataset following the [tutorial](https:... | datasets/docs/source/object_detection.mdx/0 | {
"file_path": "datasets/docs/source/object_detection.mdx",
"repo_id": "datasets",
"token_count": 2299
} | 59 |
# Preprocess
In addition to loading datasets, 🤗 Datasets other main goal is to offer a diverse set of preprocessing functions to get a dataset into an appropriate format for training with your machine learning framework.
There are many possible ways to preprocess a dataset, and it all depends on your specific datas... | datasets/docs/source/use_dataset.mdx/0 | {
"file_path": "datasets/docs/source/use_dataset.mdx",
"repo_id": "datasets",
"token_count": 3384
} | 60 |
# Copyright 2020 The HuggingFace Datasets Authors and the TensorFlow Datasets Authors.
#
# 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
#
# U... | datasets/src/datasets/arrow_reader.py/0 | {
"file_path": "datasets/src/datasets/arrow_reader.py",
"repo_id": "datasets",
"token_count": 10448
} | 61 |
import copy
from dataclasses import dataclass, field
from pathlib import Path
from typing import Any, Dict, Optional, Union
from .. import config
@dataclass
class DownloadConfig:
"""Configuration for our cached path manager.
Attributes:
cache_dir (`str` or `Path`, *optional*):
Specify a ... | datasets/src/datasets/download/download_config.py/0 | {
"file_path": "datasets/src/datasets/download/download_config.py",
"repo_id": "datasets",
"token_count": 1457
} | 62 |
# Copyright 2020 The HuggingFace Authors.
#
# 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 to... | datasets/src/datasets/formatting/np_formatter.py/0 | {
"file_path": "datasets/src/datasets/formatting/np_formatter.py",
"repo_id": "datasets",
"token_count": 2143
} | 63 |
import asyncio
import copy
import inspect
import itertools
import sys
from collections import Counter
from copy import deepcopy
from dataclasses import dataclass
from functools import partial
from itertools import cycle, islice
from typing import TYPE_CHECKING, Any, Callable, Dict, Iterable, Iterator, List, Optional, T... | datasets/src/datasets/iterable_dataset.py/0 | {
"file_path": "datasets/src/datasets/iterable_dataset.py",
"repo_id": "datasets",
"token_count": 68210
} | 64 |
from dataclasses import dataclass
from typing import Callable, Optional
import datasets
@dataclass
class GeneratorConfig(datasets.BuilderConfig):
generator: Optional[Callable] = None
gen_kwargs: Optional[dict] = None
features: Optional[datasets.Features] = None
split: datasets.NamedSplit = datasets.S... | datasets/src/datasets/packaged_modules/generator/generator.py/0 | {
"file_path": "datasets/src/datasets/packaged_modules/generator/generator.py",
"repo_id": "datasets",
"token_count": 396
} | 65 |
from typing import List
import datasets
from ..folder_based_builder import folder_based_builder
logger = datasets.utils.logging.get_logger(__name__)
class VideoFolderConfig(folder_based_builder.FolderBasedBuilderConfig):
"""BuilderConfig for ImageFolder."""
drop_labels: bool = None
drop_metadata: boo... | datasets/src/datasets/packaged_modules/videofolder/videofolder.py/0 | {
"file_path": "datasets/src/datasets/packaged_modules/videofolder/videofolder.py",
"repo_id": "datasets",
"token_count": 285
} | 66 |
import enum
import inspect
import warnings
from functools import wraps
from typing import Callable, Optional
from .logging import get_logger
_emitted_deprecation_warnings = set()
logger = get_logger(__name__)
def deprecated(help_message: Optional[str] = None):
"""Decorator to mark a class or a function as depr... | datasets/src/datasets/utils/deprecation_utils.py/0 | {
"file_path": "datasets/src/datasets/utils/deprecation_utils.py",
"repo_id": "datasets",
"token_count": 1426
} | 67 |
name: "" # Filename comes here
allow_empty: false
allow_empty_text: true
subsections:
- name: "Dataset Card for X" # First-level markdown heading
allow_empty: false
allow_empty_text: true
subsections:
- name: "Table of Contents"
allow_empty: false
allow_empty_text: false
subs... | datasets/src/datasets/utils/resources/readme_structure.yaml/0 | {
"file_path": "datasets/src/datasets/utils/resources/readme_structure.yaml",
"repo_id": "datasets",
"token_count": 1924
} | 68 |
import pytest
DATASET_LOADING_SCRIPT_NAME = "__dummy_dataset1__"
DATASET_LOADING_SCRIPT_CODE = """
import json
import os
import datasets
REPO_URL = "https://huggingface.co/datasets/hf-internal-testing/raw_jsonl/resolve/main/"
URLS = {"train": REPO_URL + "wikiann-bn-train.jsonl", "validation": REPO_URL + "wikiann-... | datasets/tests/commands/conftest.py/0 | {
"file_path": "datasets/tests/commands/conftest.py",
"repo_id": "datasets",
"token_count": 1193
} | 69 |
import os
import tarfile
import warnings
from io import BytesIO
import numpy as np
import pandas as pd
import pyarrow as pa
import pytest
from datasets import Dataset, Features, Image, Sequence, Value, concatenate_datasets, load_dataset
from datasets.features.image import encode_np_array, image_to_bytes
from ..utils... | datasets/tests/features/test_image.py/0 | {
"file_path": "datasets/tests/features/test_image.py",
"repo_id": "datasets",
"token_count": 11833
} | 70 |
import pyarrow as pa
import pytest
from datasets.builder import InvalidConfigName
from datasets.data_files import DataFilesList
from datasets.packaged_modules.arrow.arrow import Arrow, ArrowConfig
@pytest.fixture
def arrow_file_streaming_format(tmp_path):
filename = tmp_path / "stream.arrow"
testdata = [[1, ... | datasets/tests/packaged_modules/test_arrow.py/0 | {
"file_path": "datasets/tests/packaged_modules/test_arrow.py",
"repo_id": "datasets",
"token_count": 873
} | 71 |
import importlib
import os
import tempfile
import types
from contextlib import nullcontext as does_not_raise
from multiprocessing import Process
from pathlib import Path
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
from... | datasets/tests/test_builder.py/0 | {
"file_path": "datasets/tests/test_builder.py",
"repo_id": "datasets",
"token_count": 25355
} | 72 |
import pytest
import datasets.config
from datasets.utils.info_utils import is_small_dataset
@pytest.mark.parametrize("dataset_size", [None, 400 * 2**20, 600 * 2**20])
@pytest.mark.parametrize("input_in_memory_max_size", ["default", 0, 100 * 2**20, 900 * 2**20])
def test_is_small_dataset(dataset_size, input_in_memory... | datasets/tests/test_info_utils.py/0 | {
"file_path": "datasets/tests/test_info_utils.py",
"repo_id": "datasets",
"token_count": 366
} | 73 |
import pytest
from datasets.utils.version import Version
@pytest.mark.parametrize(
"other, expected_equality",
[
(Version("1.0.0"), True),
("1.0.0", True),
(Version("2.0.0"), False),
("2.0.0", False),
("1", False),
("a", False),
(1, False),
(Non... | datasets/tests/test_version.py/0 | {
"file_path": "datasets/tests/test_version.py",
"repo_id": "datasets",
"token_count": 254
} | 74 |
import argparse
import sys
sys.path.append(".")
from base_classes import LCMLoRATextToImageBenchmark # noqa: E402
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument(
"--ckpt",
type=str,
default="stabilityai/stable-diffusion-xl-base-1.0",
)
pars... | diffusers/benchmarks/benchmark_t2i_lcm_lora.py/0 | {
"file_path": "diffusers/benchmarks/benchmark_t2i_lcm_lora.py",
"repo_id": "diffusers",
"token_count": 273
} | 75 |
<!--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... | diffusers/docs/TRANSLATING.md/0 | {
"file_path": "diffusers/docs/TRANSLATING.md",
"repo_id": "diffusers",
"token_count": 1100
} | 76 |
<!--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 applica... | diffusers/docs/source/en/api/pipelines/cogview4.md/0 | {
"file_path": "diffusers/docs/source/en/api/pipelines/cogview4.md",
"repo_id": "diffusers",
"token_count": 429
} | 77 |
<!--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 to... | diffusers/docs/source/en/api/pipelines/shap_e.md/0 | {
"file_path": "diffusers/docs/source/en/api/pipelines/shap_e.md",
"repo_id": "diffusers",
"token_count": 590
} | 78 |
<!--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... | diffusers/docs/source/en/api/schedulers/ddim.md/0 | {
"file_path": "diffusers/docs/source/en/api/schedulers/ddim.md",
"repo_id": "diffusers",
"token_count": 1122
} | 79 |
<!--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... | diffusers/docs/source/en/api/schedulers/lms_discrete.md/0 | {
"file_path": "diffusers/docs/source/en/api/schedulers/lms_discrete.md",
"repo_id": "diffusers",
"token_count": 335
} | 80 |
<!--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... | diffusers/docs/source/en/optimization/open_vino.md/0 | {
"file_path": "diffusers/docs/source/en/optimization/open_vino.md",
"repo_id": "diffusers",
"token_count": 1115
} | 81 |
# Create a dataset for training
There are many datasets on the [Hub](https://huggingface.co/datasets?task_categories=task_categories:text-to-image&sort=downloads) to train a model on, but if you can't find one you're interested in or want to use your own, you can create a dataset with the 🤗 [Datasets](https://hugging... | diffusers/docs/source/en/training/create_dataset.md/0 | {
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<!--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... | diffusers/docs/source/en/tutorials/autopipeline.md/0 | {
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<!--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... | diffusers/docs/source/en/using-diffusers/image_quality.md/0 | {
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<!--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... | diffusers/docs/source/en/using-diffusers/reusing_seeds.md/0 | {
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<!--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... | diffusers/docs/source/ja/installation.md/0 | {
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