text stringlengths 5 409k | id stringlengths 14 178 | metadata dict | __index_level_0__ int64 0 572 |
|---|---|---|---|
# 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 applicabl... | accelerate/benchmarks/big_model_inference/measures_util.py/0 | {
"file_path": "accelerate/benchmarks/big_model_inference/measures_util.py",
"repo_id": "accelerate",
"token_count": 1146
} | 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/transformer_engine/distrib_deepspeed.py/0 | {
"file_path": "accelerate/benchmarks/fp8/transformer_engine/distrib_deepspeed.py",
"repo_id": "accelerate",
"token_count": 3034
} | 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/basic_tutorials/overview.md/0 | {
"file_path": "accelerate/docs/source/basic_tutorials/overview.md",
"repo_id": "accelerate",
"token_count": 303
} | 2 |
<!--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 applicable law or agreed... | accelerate/docs/source/package_reference/big_modeling.md/0 | {
"file_path": "accelerate/docs/source/package_reference/big_modeling.md",
"repo_id": "accelerate",
"token_count": 712
} | 3 |
<!--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/usage_guides/checkpoint.md/0 | {
"file_path": "accelerate/docs/source/usage_guides/checkpoint.md",
"repo_id": "accelerate",
"token_count": 1150
} | 4 |
<!--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 applicable law or agreed... | accelerate/docs/source/usage_guides/sagemaker.md/0 | {
"file_path": "accelerate/docs/source/usage_guides/sagemaker.md",
"repo_id": "accelerate",
"token_count": 2220
} | 5 |
{
"fp16": {
"enabled": true,
"loss_scale": 0,
"loss_scale_window": 1000,
"initial_scale_power": 16,
"hysteresis": 2,
"min_loss_scale": 1
},
"optimizer": {
"type": "AdamW",
"params": {
"lr": "auto",
"weight_decay": "auto"... | accelerate/examples/deepspeed_config_templates/zero_stage1_config.json/0 | {
"file_path": "accelerate/examples/deepspeed_config_templates/zero_stage1_config.json",
"repo_id": "accelerate",
"token_count": 614
} | 6 |
# 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/pippy/t5.py/0 | {
"file_path": "accelerate/examples/inference/pippy/t5.py",
"repo_id": "accelerate",
"token_count": 1023
} | 7 |
# 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 applicabl... | accelerate/manim_animations/dataloaders/stage_2.py/0 | {
"file_path": "accelerate/manim_animations/dataloaders/stage_2.py",
"repo_id": "accelerate",
"token_count": 3396
} | 8 |
#!/usr/bin/env python
# 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
#
# Unles... | accelerate/src/accelerate/commands/config/config.py/0 | {
"file_path": "accelerate/src/accelerate/commands/config/config.py",
"repo_id": "accelerate",
"token_count": 1067
} | 9 |
#!/usr/bin/env python
# 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
#
# Unles... | accelerate/src/accelerate/commands/test.py/0 | {
"file_path": "accelerate/src/accelerate/commands/test.py",
"repo_id": "accelerate",
"token_count": 755
} | 10 |
# 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/test_utils/testing.py/0 | {
"file_path": "accelerate/src/accelerate/test_utils/testing.py",
"repo_id": "accelerate",
"token_count": 8761
} | 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/src/accelerate/utils/offload.py/0 | {
"file_path": "accelerate/src/accelerate/utils/offload.py",
"repo_id": "accelerate",
"token_count": 3177
} | 12 |
# 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/fsdp/test_fsdp.py/0 | {
"file_path": "accelerate/tests/fsdp/test_fsdp.py",
"repo_id": "accelerate",
"token_count": 9529
} | 13 |
# 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/tests/test_grad_sync.py/0 | {
"file_path": "accelerate/tests/test_grad_sync.py",
"repo_id": "accelerate",
"token_count": 579
} | 14 |
# 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/tests/test_scheduler.py/0 | {
"file_path": "accelerate/tests/test_scheduler.py",
"repo_id": "accelerate",
"token_count": 2536
} | 15 |
import json
from pathlib import Path
from datasets import Dataset
from huggingface_hub import HfApi
ORG_NAME = "agents-course"
def main():
"""Push quiz questions to the Hugging Face Hub"""
for file in Path("data").glob("*.json"):
print(f"Processing {file}")
with open(file, "r") as f:
... | agents-course/quiz/push_questions.py/0 | {
"file_path": "agents-course/quiz/push_questions.py",
"repo_id": "agents-course",
"token_count": 319
} | 16 |
# Conclusion [[conclusion]]
Congratulations on finishing this first Unit 🥳
You've just **mastered the fundamentals of Agents** and you've created your first AI Agent!
It's **normal if you still feel confused by some of these elements**. Agents are a complex topic and it's common to take a while to grasp everything.... | agents-course/units/en/unit1/conclusion.mdx/0 | {
"file_path": "agents-course/units/en/unit1/conclusion.mdx",
"repo_id": "agents-course",
"token_count": 368
} | 17 |
[build]
rustflags = ["-C", "target-cpu=native"]
[target.wasm32-unknown-unknown]
rustflags = ["-C", "target-feature=+simd128"]
[target.x86_64-apple-darwin]
rustflags = ["-C", "target-feature=-avx,-avx2"] | candle/.cargo/config.toml/0 | {
"file_path": "candle/.cargo/config.toml",
"repo_id": "candle",
"token_count": 84
} | 18 |
# Introduction
{{#include ../../README.md:features}}
This book will introduce step by step how to use `candle`.
| candle/candle-book/src/README.md/0 | {
"file_path": "candle/candle-book/src/README.md",
"repo_id": "candle",
"token_count": 34
} | 19 |
# Porting a custom kernel
| candle/candle-book/src/inference/cuda/porting.md/0 | {
"file_path": "candle/candle-book/src/inference/cuda/porting.md",
"repo_id": "candle",
"token_count": 7
} | 20 |
use crate::benchmarks::{BenchDevice, BenchDeviceHandler};
use candle_core::{DType, Device, Tensor};
use criterion::{black_box, criterion_group, Criterion, Throughput};
use std::time::Instant;
fn run(
x: &Tensor,
k: &Tensor,
padding: usize,
output_padding: usize,
stride: usize,
dilation: usize,
... | candle/candle-core/benches/benchmarks/conv_transpose2d.rs/0 | {
"file_path": "candle/candle-core/benches/benchmarks/conv_transpose2d.rs",
"repo_id": "candle",
"token_count": 826
} | 21 |
//! Implement conversion traits for tensors
use crate::{DType, Device, Error, Tensor, WithDType};
use half::{bf16, f16, slice::HalfFloatSliceExt};
use std::convert::TryFrom;
impl<T: WithDType> TryFrom<&Tensor> for Vec<T> {
type Error = Error;
fn try_from(tensor: &Tensor) -> Result<Self, Self::Error> {
... | candle/candle-core/src/convert.rs/0 | {
"file_path": "candle/candle-core/src/convert.rs",
"repo_id": "candle",
"token_count": 2242
} | 22 |
//! Pretty printing of tensors
//!
//! This implementation should be in line with the [PyTorch version](https://github.com/pytorch/pytorch/blob/7b419e8513a024e172eae767e24ec1b849976b13/torch/_tensor_str.py).
//!
use crate::{DType, Result, Tensor, WithDType};
use half::{bf16, f16};
impl Tensor {
fn fmt_dt<T: WithDT... | candle/candle-core/src/display.rs/0 | {
"file_path": "candle/candle-core/src/display.rs",
"repo_id": "candle",
"token_count": 9761
} | 23 |
#![allow(unused)]
use super::GgmlDType;
use crate::{CudaDevice, CudaStorage, Error, Result};
pub struct QCudaStorage {
dtype: GgmlDType,
device: CudaDevice,
}
impl QCudaStorage {
pub fn zeros(_: &CudaDevice, _: usize, _: GgmlDType) -> Result<Self> {
Err(Error::NotCompiledWithCudaSupport)
}
... | candle/candle-core/src/quantized/dummy_cuda.rs/0 | {
"file_path": "candle/candle-core/src/quantized/dummy_cuda.rs",
"repo_id": "candle",
"token_count": 594
} | 24 |
use crate::Layout;
/// An iterator over offset position for items of an N-dimensional arrays stored in a
/// flat buffer using some potential strides.
#[derive(Debug)]
pub struct StridedIndex<'a> {
next_storage_index: Option<usize>,
multi_index: Vec<usize>,
dims: &'a [usize],
stride: &'a [usize],
}
im... | candle/candle-core/src/strided_index.rs/0 | {
"file_path": "candle/candle-core/src/strided_index.rs",
"repo_id": "candle",
"token_count": 1094
} | 25 |
import torch
from collections import OrderedDict
# Write a trivial tensor to a pt file
a= torch.tensor([[1,2,3,4], [5,6,7,8]])
o = OrderedDict()
o["test"] = a
# Write a trivial tensor to a pt file
torch.save(o, "test.pt")
###############################################################################################... | candle/candle-core/tests/pth.py/0 | {
"file_path": "candle/candle-core/tests/pth.py",
"repo_id": "candle",
"token_count": 441
} | 26 |
//! The CIFAR-10 dataset.
//!
//! The files can be downloaded from the following page:
//! <https://www.cs.toronto.edu/~kriz/cifar.html>
//! The binary version of the dataset is used.
use crate::vision::Dataset;
use candle::{DType, Device, Error, Result, Tensor};
use hf_hub::{api::sync::Api, Repo, RepoType};
use parque... | candle/candle-datasets/src/vision/cifar.rs/0 | {
"file_path": "candle/candle-datasets/src/vision/cifar.rs",
"repo_id": "candle",
"token_count": 2139
} | 27 |
#[cfg(feature = "mkl")]
extern crate intel_mkl_src;
#[cfg(feature = "accelerate")]
extern crate accelerate_src;
use anyhow::{Error as E, Result};
use clap::Parser;
use candle_transformers::models::chatglm::{Config, Model};
use candle::{DType, Device, Tensor};
use candle_nn::VarBuilder;
use candle_transformers::gene... | candle/candle-examples/examples/chatglm/main.rs/0 | {
"file_path": "candle/candle-examples/examples/chatglm/main.rs",
"repo_id": "candle",
"token_count": 3423
} | 28 |
#[cfg(feature = "mkl")]
extern crate intel_mkl_src;
#[cfg(feature = "accelerate")]
extern crate accelerate_src;
use std::fmt::Display;
use std::path::PathBuf;
use anyhow::bail;
use anyhow::{Error as E, Result};
use candle::{Device, Tensor};
use candle_nn::ops::softmax;
use candle_nn::VarBuilder;
use candle_transform... | candle/candle-examples/examples/debertav2/main.rs/0 | {
"file_path": "candle/candle-examples/examples/debertav2/main.rs",
"repo_id": "candle",
"token_count": 6817
} | 29 |
use anyhow::{Context, Result};
use std::sync::{Arc, Mutex};
pub const SAMPLE_RATE: usize = 24_000;
pub(crate) struct AudioOutputData_ {
resampled_data: std::collections::VecDeque<f32>,
resampler: rubato::FastFixedIn<f32>,
output_buffer: Vec<f32>,
input_buffer: Vec<f32>,
input_len: usize,
}
impl A... | candle/candle-examples/examples/encodec/audio_io.rs/0 | {
"file_path": "candle/candle-examples/examples/encodec/audio_io.rs",
"repo_id": "candle",
"token_count": 4796
} | 30 |
use candle::{DType, Device, Tensor};
use candle_nn::VarBuilder;
use candle_transformers::generation::LogitsProcessor;
use candle_transformers::models::glm4::*;
use clap::Parser;
use hf_hub::{Repo, RepoType};
use tokenizers::Tokenizer;
struct TextGeneration {
model: Model,
device: Device,
tokenizer: Tokenize... | candle/candle-examples/examples/glm4/main.rs/0 | {
"file_path": "candle/candle-examples/examples/glm4/main.rs",
"repo_id": "candle",
"token_count": 3621
} | 31 |
pub const DEFAULT_IMAGE_TOKEN: &str = "<image>";
pub const DEFAULT_IM_START_TOKEN: &str = "<im_start>";
pub const DEFAULT_IM_END_TOKEN: &str = "<im_end>";
pub const IMAGE_PLACEHOLDER: &str = "<image-placeholder>";
| candle/candle-examples/examples/llava/constants.rs/0 | {
"file_path": "candle/candle-examples/examples/llava/constants.rs",
"repo_id": "candle",
"token_count": 86
} | 32 |
#[cfg(feature = "mkl")]
extern crate intel_mkl_src;
#[cfg(feature = "accelerate")]
extern crate accelerate_src;
use anyhow::{Error as E, Result};
use clap::Parser;
use candle::{DType, Device, Tensor};
use candle_nn::VarBuilder;
use candle_transformers::{
generation::LogitsProcessor,
models::{moondream, quant... | candle/candle-examples/examples/moondream/main.rs/0 | {
"file_path": "candle/candle-examples/examples/moondream/main.rs",
"repo_id": "candle",
"token_count": 5490
} | 33 |
#[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_examples::token_output_stream::TokenOutputStream;
use candle_transformers::models::mixformer::{Config, MixFormerSequentialForCaus... | candle/candle-examples/examples/phi/main.rs/0 | {
"file_path": "candle/candle-examples/examples/phi/main.rs",
"repo_id": "candle",
"token_count": 9478
} | 34 |
import gymnasium as gym
import numpy as np
from collections import deque
from PIL import Image
from multiprocessing import Process, Pipe
# atari_wrappers.py
class NoopResetEnv(gym.Wrapper):
def __init__(self, env, noop_max=30):
"""Sample initial states by taking random number of no-ops on reset.
No... | candle/candle-examples/examples/reinforcement-learning/atari_wrappers.py/0 | {
"file_path": "candle/candle-examples/examples/reinforcement-learning/atari_wrappers.py",
"repo_id": "candle",
"token_count": 4740
} | 35 |
# candle-segformer
- [HuggingFace Segformer Model Card][segformer]
- [`mit-b0` - An encoder only pretrained model][encoder]
- [`segformer-b0-finetuned-ade-512-512` - A fine tuned model for segmentation][ade512]
## How to run the example
If you want you can use the example images from this [pull request][pr], downloa... | candle/candle-examples/examples/segformer/README.md/0 | {
"file_path": "candle/candle-examples/examples/segformer/README.md",
"repo_id": "candle",
"token_count": 357
} | 36 |
use anyhow::{Error as E, Ok, Result};
use candle::{DType, IndexOp, Module, Tensor, D};
use candle_transformers::models::{stable_diffusion, t5};
use std::path::PathBuf;
use tokenizers::tokenizer::Tokenizer;
struct ClipWithTokenizer {
clip: stable_diffusion::clip::ClipTextTransformer,
config: stable_diffusion::c... | candle/candle-examples/examples/stable-diffusion-3/clip.rs/0 | {
"file_path": "candle/candle-examples/examples/stable-diffusion-3/clip.rs",
"repo_id": "candle",
"token_count": 4060
} | 37 |
use image::{DynamicImage, ImageBuffer};
use serde::Deserialize;
use std::collections::HashMap;
use candle::{DType, Device, Result, Tensor};
#[derive(Debug, Clone, PartialEq, Deserialize)]
pub struct ProcessorConfig {
do_resize: bool,
height: u32,
width: u32,
do_rescale: bool,
do_normalize: bool,
... | candle/candle-examples/examples/trocr/image_processor.rs/0 | {
"file_path": "candle/candle-examples/examples/trocr/image_processor.rs",
"repo_id": "candle",
"token_count": 2273
} | 38 |
# candle-wuerstchen: Efficient Pretraining of Text-to-Image Models
The `wuerstchen` example is a port of the [diffusers
implementation](https://github.com/huggingface/diffusers/tree/19edca82f1ff194c07317369a92b470dbae97f34/src/diffusers/pipelines/wuer... | candle/candle-examples/examples/wuerstchen/README.md/0 | {
"file_path": "candle/candle-examples/examples/wuerstchen/README.md",
"repo_id": "candle",
"token_count": 358
} | 39 |
use candle::{DType, IndexOp, Result, Tensor, D};
use candle_nn::{batch_norm, conv2d, conv2d_no_bias, Conv2d, Conv2dConfig, Module, VarBuilder};
#[derive(Clone, Copy, PartialEq, Debug)]
pub struct Multiples {
depth: f64,
width: f64,
ratio: f64,
}
impl Multiples {
pub fn n() -> Self {
Self {
... | candle/candle-examples/examples/yolo-v8/model.rs/0 | {
"file_path": "candle/candle-examples/examples/yolo-v8/model.rs",
"repo_id": "candle",
"token_count": 12422
} | 40 |
/******************************************************************************
* Copyright (c) 2023, Tri Dao.
******************************************************************************/
#pragma once
#include <cuda.h>
#include <vector>
// #include <ATen/cuda/CUDAGeneratorImpl.h> // For at::Generator and at::Ph... | candle/candle-flash-attn/kernels/flash.h/0 | {
"file_path": "candle/candle-flash-attn/kernels/flash.h",
"repo_id": "candle",
"token_count": 2326
} | 41 |
mod ffi;
use candle::backend::BackendStorage;
use candle::cuda_backend::cudarc::driver::DevicePtr;
use candle::cuda_backend::WrapErr;
use candle::{CpuStorage, DType, Layout, Result, Shape, Tensor};
use half::{bf16, f16};
pub struct FlashAttn {
pub softmax_scale: f32,
pub alibi_slopes: Option<Tensor>,
pub ... | candle/candle-flash-attn/src/lib.rs/0 | {
"file_path": "candle/candle-flash-attn/src/lib.rs",
"repo_id": "candle",
"token_count": 17752
} | 42 |
#include "cuda_utils.cuh"
#include <cmath>
#include <stdint.h>
#define WARP_SIZE 32
const int BLOCK_SIZE = 1024;
// TODO: Maybe add some fast_sum_f16_f32 variant that not only accumulate in f32
// but also expect a f32 output so that this can be used for normalization e.g.
// in softmax.
// Fast reduce sum kernel, t... | candle/candle-kernels/src/reduce.cu/0 | {
"file_path": "candle/candle-kernels/src/reduce.cu",
"repo_id": "candle",
"token_count": 12783
} | 43 |
// The implementation below comes from MLX.
// https://github.com/ml-explore/mlx/blob/0cea88bcc5e98e81a24d92eed8870a6976999f05/mlx/backend/metal/kernels/sort.h
// Copyright © 2023-2024 Apple Inc.
#define MLX_MTL_CONST static constant constexpr const
#define MLX_MTL_LOOP_UNROLL _Pragma("clang loop unroll(full)")
#incl... | candle/candle-metal-kernels/src/mlx_sort.metal/0 | {
"file_path": "candle/candle-metal-kernels/src/mlx_sort.metal",
"repo_id": "candle",
"token_count": 12675
} | 44 |
[package]
name = "candle-nn"
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]
accelerate-src = { workspace = true, optional = true }
candle = { wo... | candle/candle-nn/Cargo.toml/0 | {
"file_path": "candle/candle-nn/Cargo.toml",
"repo_id": "candle",
"token_count": 371
} | 45 |
//! Variable initialization.
// This is based on:
// https://github.com/pytorch/pytorch/blob/07107919297db3f8ab37f11c12666b6d6d5f692e/torch/nn/init.py#
use candle::{DType, Device, Result, Shape, Tensor, Var};
/// Number of features as input or output of a layer.
/// In Kaiming initialization, choosing `FanIn` preserve... | candle/candle-nn/src/init.rs/0 | {
"file_path": "candle/candle-nn/src/init.rs",
"repo_id": "candle",
"token_count": 2212
} | 46 |
#[cfg(feature = "mkl")]
extern crate intel_mkl_src;
#[cfg(feature = "accelerate")]
extern crate accelerate_src;
use anyhow::Result;
use candle::{test_utils, Device, Tensor};
use candle_nn::{LayerNorm, Module};
#[test]
fn layer_norm() -> Result<()> {
let device = &Device::Cpu;
let w = Tensor::new(&[3f32], dev... | candle/candle-nn/tests/layer_norm.rs/0 | {
"file_path": "candle/candle-nn/tests/layer_norm.rs",
"repo_id": "candle",
"token_count": 892
} | 47 |
## Installation
From the `candle-pyo3` directory, enable a virtual env where you will want the
candle package to be installed then run.
```bash
maturin develop -r
python test.py
```
## Generating Stub Files for Type Hinting
For type hinting support, the `candle-pyo3` package requires `*.pyi` files. You can automa... | candle/candle-pyo3/README.md/0 | {
"file_path": "candle/candle-pyo3/README.md",
"repo_id": "candle",
"token_count": 190
} | 48 |
import candle
from candle import Tensor
from .module import Module
from typing import Union, List, Tuple, Optional, Any
_shape_t = Union[int, List[int]]
import numbers
class LayerNorm(Module):
r"""Applies Layer Normalization over a mini-batch of inputs as described in
the paper `Layer Normalization <https://... | candle/candle-pyo3/py_src/candle/nn/normalization.py/0 | {
"file_path": "candle/candle-pyo3/py_src/candle/nn/normalization.py",
"repo_id": "candle",
"token_count": 803
} | 49 |
import candle
import torch
# convert from candle tensor to torch tensor
t = candle.randn((3, 512, 512))
torch_tensor = t.to_torch()
print(torch_tensor)
print(type(torch_tensor))
# convert from torch tensor to candle tensor
t = torch.randn((3, 512, 512))
candle_tensor = candle.Tensor(t)
print(candle_tensor)
print(type... | candle/candle-pyo3/test_pytorch.py/0 | {
"file_path": "candle/candle-pyo3/test_pytorch.py",
"repo_id": "candle",
"token_count": 126
} | 50 |
//! Based on the BLIP paper from Salesforce Research.
//!
//! The blip-image-captioning model can generate captions for an input image.
//!
//! - ⚡ [Interactive Wasm Example](https://huggingface.co/spaces/radames/Candle-BLIP-Image-Captioning)
//! - 💻 [GH Link](https://github.com/salesforce/BLIP)
//! - 🤗 [HF Link](htt... | candle/candle-transformers/src/models/blip.rs/0 | {
"file_path": "candle/candle-transformers/src/models/blip.rs",
"repo_id": "candle",
"token_count": 4762
} | 51 |
//! Implementation of the Depth Anything model from FAIR.
//!
//! See:
//! - ["Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data"](https://github.com/LiheYoung/Depth-Anything)
//!
use std::sync::Arc;
use candle::D::Minus1;
use candle::{Module, Result, Tensor};
use candle_nn::ops::Identity;
use candle... | candle/candle-transformers/src/models/depth_anything_v2.rs/0 | {
"file_path": "candle/candle-transformers/src/models/depth_anything_v2.rs",
"repo_id": "candle",
"token_count": 9140
} | 52 |
// Copyright (c) Kyutai, all rights reserved.
// This source code is licensed under the license found in the
// LICENSE file in the root directory of this source tree.
use super::{conv, quantization, seanet, transformer};
use candle::{DType, Device, Module, Result, StreamTensor, StreamingModule, Tensor};
use candle_nn... | candle/candle-transformers/src/models/mimi/encodec.rs/0 | {
"file_path": "candle/candle-transformers/src/models/mimi/encodec.rs",
"repo_id": "candle",
"token_count": 3773
} | 53 |
//! Candle implementations for various deep learning models
//!
//! This crate provides implementations of popular machine learning models and architectures for different modalities.
//!
//! - Large language models: [`llama`], [`phi3`], [`mamba`], [`mixtral`], [`bert`], ...
//! - Text to text models: [`t5`], ...
//! ... | candle/candle-transformers/src/models/mod.rs/0 | {
"file_path": "candle/candle-transformers/src/models/mod.rs",
"repo_id": "candle",
"token_count": 1066
} | 54 |
//! Pixtral Language-Image Pre-Training
//!
//! Pixtral is an architecture trained for multimodal learning
//! using images paired with text descriptions.
//!
//! - 💻 Transformers Python [reference implementation](https://github.com/huggingface/transformers/tree/main/src/transformers/models/pixtral)
//! - 📝 [Blog Pos... | candle/candle-transformers/src/models/pixtral/mod.rs/0 | {
"file_path": "candle/candle-transformers/src/models/pixtral/mod.rs",
"repo_id": "candle",
"token_count": 578
} | 55 |
//! RWKV v6 model implementation with quantization support.
//!
//! RWKV is a linear attention model that combines the efficiency of RNNs
//! with the parallelizable training of Transformers. Version 6 builds on previous
//! versions with further optimizations.
//!
//! Key characteristics:
//! - Linear attention mechan... | candle/candle-transformers/src/models/quantized_rwkv_v6.rs/0 | {
"file_path": "candle/candle-transformers/src/models/quantized_rwkv_v6.rs",
"repo_id": "candle",
"token_count": 6677
} | 56 |
// Adapted from:
// https://github.com/ChaoningZhang/MobileSAM/blob/master/mobile_sam/modeling/tiny_vit_sam.py
use candle::{IndexOp, Result, Tensor, D};
use candle_nn::{Conv2dConfig, Module, VarBuilder};
const MBCONV_EXPAND_RATIO: usize = 4;
const MLP_RATIO: usize = 4;
const LOCAL_CONV_SIZE: usize = 3;
const IMG_SIZE:... | candle/candle-transformers/src/models/segment_anything/tiny_vit.rs/0 | {
"file_path": "candle/candle-transformers/src/models/segment_anything/tiny_vit.rs",
"repo_id": "candle",
"token_count": 10372
} | 57 |
#![allow(dead_code)]
//! # Variational Auto-Encoder (VAE) Models.
//!
//! Auto-encoder models compress their input to a usually smaller latent space
//! before expanding it back to its original shape. This results in the latent values
//! compressing the original information.
use super::unet_2d_blocks::{
DownEncode... | candle/candle-transformers/src/models/stable_diffusion/vae.rs/0 | {
"file_path": "candle/candle-transformers/src/models/stable_diffusion/vae.rs",
"repo_id": "candle",
"token_count": 6467
} | 58 |
use super::common::{AttnBlock, GlobalResponseNorm, LayerNormNoWeights, TimestepBlock, WLayerNorm};
use candle::{DType, Module, Result, Tensor, D};
use candle_nn::VarBuilder;
#[derive(Debug)]
pub struct ResBlockStageB {
depthwise: candle_nn::Conv2d,
norm: WLayerNorm,
channelwise_lin1: candle_nn::Linear,
... | candle/candle-transformers/src/models/wuerstchen/diffnext.rs/0 | {
"file_path": "candle/candle-transformers/src/models/wuerstchen/diffnext.rs",
"repo_id": "candle",
"token_count": 8148
} | 59 |
//load Candle Bert Module wasm module
import init, { Model } from "./build/m.js";
async function fetchArrayBuffer(url) {
const cacheName = "bert-candle-cache";
const cache = await caches.open(cacheName);
const cachedResponse = await cache.match(url);
if (cachedResponse) {
const data = await cachedResponse.... | candle/candle-wasm-examples/bert/bertWorker.js/0 | {
"file_path": "candle/candle-wasm-examples/bert/bertWorker.js",
"repo_id": "candle",
"token_count": 779
} | 60 |
import init, { Model } from "./build/m.js";
async function fetchArrayBuffer(url, cacheModel = true) {
if (!cacheModel)
return new Uint8Array(await (await fetch(url)).arrayBuffer());
const cacheName = "moondream-candle-cache";
const cache = await caches.open(cacheName);
const cachedResponse = await cache.ma... | candle/candle-wasm-examples/moondream/moondreamWorker.js/0 | {
"file_path": "candle/candle-wasm-examples/moondream/moondreamWorker.js",
"repo_id": "candle",
"token_count": 2273
} | 61 |
import init, { run_app } from './pkg/candle_wasm_example_whisper.js';
async function main() {
await init('/pkg/candle_wasm_example_whisper_bg.wasm');
run_app();
}
main()
| candle/candle-wasm-examples/whisper/main.js/0 | {
"file_path": "candle/candle-wasm-examples/whisper/main.js",
"repo_id": "candle",
"token_count": 73
} | 62 |
fn main() {
wasm_logger::init(wasm_logger::Config::new(log::Level::Trace));
console_error_panic_hook::set_once();
yew::Renderer::<candle_wasm_example_yolo::App>::new().render();
}
| candle/candle-wasm-examples/yolo/src/bin/app.rs/0 | {
"file_path": "candle/candle-wasm-examples/yolo/src/bin/app.rs",
"repo_id": "candle",
"token_count": 82
} | 63 |
# How to add one new datasets
Add datasets directly to the 🤗 Hugging Face Hub!
You can share your dataset on https://huggingface.co/datasets directly using your account, see the documentation:
* [Create a dataset and upload files on the website](https://huggingface.co/docs/datasets/upload_dataset)
* [Advanced guide... | datasets/ADD_NEW_DATASET.md/0 | {
"file_path": "datasets/ADD_NEW_DATASET.md",
"repo_id": "datasets",
"token_count": 113
} | 64 |
# Know your dataset
There are two types of dataset objects, a regular [`Dataset`] and then an ✨ [`IterableDataset`] ✨. A [`Dataset`] provides fast random access to the rows, and memory-mapping so that loading even large datasets only uses a relatively small amount of device memory. But for really, really big datasets ... | datasets/docs/source/access.mdx/0 | {
"file_path": "datasets/docs/source/access.mdx",
"repo_id": "datasets",
"token_count": 2295
} | 65 |
# Process image data
This guide shows specific methods for processing image datasets. Learn how to:
- Use [`~Dataset.map`] with image dataset.
- Apply data augmentations to a dataset with [`~Dataset.set_transform`].
For a guide on how to process any type of dataset, take a look at the <a class="underline decoration-... | datasets/docs/source/image_process.mdx/0 | {
"file_path": "datasets/docs/source/image_process.mdx",
"repo_id": "datasets",
"token_count": 1031
} | 66 |
<!--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... | datasets/docs/source/quickstart.mdx/0 | {
"file_path": "datasets/docs/source/quickstart.mdx",
"repo_id": "datasets",
"token_count": 6116
} | 67 |
# Use with Spark
This document is a quick introduction to using 🤗 Datasets with Spark, with a particular focus on how to load a Spark DataFrame into a [`Dataset`] object.
From there, you have fast access to any element and you can use it as a data loader to train models.
## Load from Spark
A [`Dataset`] object is ... | datasets/docs/source/use_with_spark.mdx/0 | {
"file_path": "datasets/docs/source/use_with_spark.mdx",
"repo_id": "datasets",
"token_count": 962
} | 68 |
#!/usr/bin/env python
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.convert_to_parquet import ConvertToParquetCommand
from datasets.commands.delete_from_hub import DeleteFromHubCommand
from datasets.commands.env import EnvironmentCommand
from datasets.c... | datasets/src/datasets/commands/datasets_cli.py/0 | {
"file_path": "datasets/src/datasets/commands/datasets_cli.py",
"repo_id": "datasets",
"token_count": 480
} | 69 |
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.download_config import DownloadConfig
from ..table import arra... | datasets/src/datasets/features/image.py/0 | {
"file_path": "datasets/src/datasets/features/image.py",
"repo_id": "datasets",
"token_count": 6987
} | 70 |
import contextlib
from multiprocessing import Pool, RLock
from tqdm.auto import tqdm
from ..utils import experimental, logging
logger = logging.get_logger(__name__)
class ParallelBackendConfig:
backend_name = None
@experimental
def parallel_map(function, iterable, num_proc, batched, batch_size, types, disab... | datasets/src/datasets/parallel/parallel.py/0 | {
"file_path": "datasets/src/datasets/parallel/parallel.py",
"repo_id": "datasets",
"token_count": 1783
} | 71 |
import enum
import os
from typing import Optional
from huggingface_hub.utils import insecure_hashlib
from .. import config
from ..exceptions import (
ExpectedMoreDownloadedFilesError,
ExpectedMoreSplitsError,
NonMatchingChecksumError,
NonMatchingSplitsSizesError,
UnexpectedDownloadedFileError,
... | datasets/src/datasets/utils/info_utils.py/0 | {
"file_path": "datasets/src/datasets/utils/info_utils.py",
"repo_id": "datasets",
"token_count": 1731
} | 72 |
import os
from typing import Dict, List, Tuple, TypeVar, Union
T = TypeVar("T")
ListLike = Union[List[T], Tuple[T, ...]]
NestedDataStructureLike = Union[T, List[T], Dict[str, T]]
PathLike = Union[str, bytes, os.PathLike]
| datasets/src/datasets/utils/typing.py/0 | {
"file_path": "datasets/src/datasets/utils/typing.py",
"repo_id": "datasets",
"token_count": 84
} | 73 |
import pytest
from datasets.builder import InvalidConfigName
from datasets.data_files import DataFilesList
from datasets.packaged_modules.pandas.pandas import PandasConfig
def test_config_raises_when_invalid_name() -> None:
with pytest.raises(InvalidConfigName, match="Bad characters"):
_ = PandasConfig(n... | datasets/tests/packaged_modules/test_pandas.py/0 | {
"file_path": "datasets/tests/packaged_modules/test_pandas.py",
"repo_id": "datasets",
"token_count": 229
} | 74 |
import unittest
import warnings
from datasets.utils import experimental
@experimental
def dummy_function():
return "success"
class TestExperimentalFlag(unittest.TestCase):
def test_experimental_warning(self):
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always"... | datasets/tests/test_experimental.py/0 | {
"file_path": "datasets/tests/test_experimental.py",
"repo_id": "datasets",
"token_count": 152
} | 75 |
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def test_patch_submodule():
import os as original_os
from os import path as original_path
from os import rename as original_rename
from os.path import dirname as original_dirname
from os.path impor... | datasets/tests/test_patching.py/0 | {
"file_path": "datasets/tests/test_patching.py",
"repo_id": "datasets",
"token_count": 2274
} | 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 applicable law or agreed... | diffusers/docs/source/en/api/configuration.md/0 | {
"file_path": "diffusers/docs/source/en/api/configuration.md",
"repo_id": "diffusers",
"token_count": 325
} | 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... | diffusers/docs/source/en/api/models/autoencoder_oobleck.md/0 | {
"file_path": "diffusers/docs/source/en/api/models/autoencoder_oobleck.md",
"repo_id": "diffusers",
"token_count": 565
} | 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 to... | diffusers/docs/source/en/api/pipelines/kandinsky3.md/0 | {
"file_path": "diffusers/docs/source/en/api/pipelines/kandinsky3.md",
"repo_id": "diffusers",
"token_count": 816
} | 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/pipelines/paint_by_example.md/0 | {
"file_path": "diffusers/docs/source/en/api/pipelines/paint_by_example.md",
"repo_id": "diffusers",
"token_count": 758
} | 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/api/pipelines/text_to_video_zero.md/0 | {
"file_path": "diffusers/docs/source/en/api/pipelines/text_to_video_zero.md",
"repo_id": "diffusers",
"token_count": 4548
} | 81 |
<!--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/installation.md/0 | {
"file_path": "diffusers/docs/source/en/installation.md",
"repo_id": "diffusers",
"token_count": 1773
} | 82 |
<!--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/quantization/bitsandbytes.md/0 | {
"file_path": "diffusers/docs/source/en/quantization/bitsandbytes.md",
"repo_id": "diffusers",
"token_count": 5098
} | 83 |
<!--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/training/lcm_distill.md/0 | {
"file_path": "diffusers/docs/source/en/training/lcm_distill.md",
"repo_id": "diffusers",
"token_count": 4595
} | 84 |
<!--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/cogvideox.md/0 | {
"file_path": "diffusers/docs/source/en/using-diffusers/cogvideox.md",
"repo_id": "diffusers",
"token_count": 1566
} | 85 |
<!--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/loading.md/0 | {
"file_path": "diffusers/docs/source/en/using-diffusers/loading.md",
"repo_id": "diffusers",
"token_count": 8605
} | 86 |
<!--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/svd.md/0 | {
"file_path": "diffusers/docs/source/en/using-diffusers/svd.md",
"repo_id": "diffusers",
"token_count": 1832
} | 87 |
<!--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/ko/conceptual/contribution.md/0 | {
"file_path": "diffusers/docs/source/ko/conceptual/contribution.md",
"repo_id": "diffusers",
"token_count": 35978
} | 88 |
<!--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/ko/quicktour.md/0 | {
"file_path": "diffusers/docs/source/ko/quicktour.md",
"repo_id": "diffusers",
"token_count": 11452
} | 89 |
<!--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/ko/using-diffusers/conditional_image_generation.md/0 | {
"file_path": "diffusers/docs/source/ko/using-diffusers/conditional_image_generation.md",
"repo_id": "diffusers",
"token_count": 1550
} | 90 |
<!--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... | diffusers/docs/source/ko/using-diffusers/svd.md/0 | {
"file_path": "diffusers/docs/source/ko/using-diffusers/svd.md",
"repo_id": "diffusers",
"token_count": 3466
} | 91 |
# Advanced diffusion training examples
## Train Dreambooth LoRA with Stable Diffusion XL
> [!TIP]
> 💡 This example follows the techniques and recommended practices covered in the blog post: [LoRA training scripts of the world, unite!](https://huggingface.co/blog/sdxl_lora_advanced_script). Make sure to check it out b... | diffusers/examples/advanced_diffusion_training/README.md/0 | {
"file_path": "diffusers/examples/advanced_diffusion_training/README.md",
"repo_id": "diffusers",
"token_count": 7219
} | 92 |
# 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 applicabl... | diffusers/examples/community/adaptive_mask_inpainting.py/0 | {
"file_path": "diffusers/examples/community/adaptive_mask_inpainting.py",
"repo_id": "diffusers",
"token_count": 30873
} | 93 |
import re
from copy import deepcopy
from dataclasses import asdict, dataclass
from enum import Enum
from typing import List, Optional, Union
import numpy as np
import torch
from numpy import exp, pi, sqrt
from torchvision.transforms.functional import resize
from tqdm.auto import tqdm
from transformers import CLIPImage... | diffusers/examples/community/mixture_canvas.py/0 | {
"file_path": "diffusers/examples/community/mixture_canvas.py",
"repo_id": "diffusers",
"token_count": 9675
} | 94 |
import inspect
import os
import numpy as np
import torch
import torch.nn.functional as nnf
from PIL import Image
from torch.optim.adam import Adam
from tqdm import tqdm
from diffusers import StableDiffusionPipeline
from diffusers.pipelines.stable_diffusion import StableDiffusionPipelineOutput
def retrieve_timesteps... | diffusers/examples/community/pipeline_null_text_inversion.py/0 | {
"file_path": "diffusers/examples/community/pipeline_null_text_inversion.py",
"repo_id": "diffusers",
"token_count": 5423
} | 95 |
# 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 applicabl... | diffusers/examples/community/rerender_a_video.py/0 | {
"file_path": "diffusers/examples/community/rerender_a_video.py",
"repo_id": "diffusers",
"token_count": 27315
} | 96 |
# 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 applicabl... | diffusers/examples/community/stable_diffusion_repaint.py/0 | {
"file_path": "diffusers/examples/community/stable_diffusion_repaint.py",
"repo_id": "diffusers",
"token_count": 19673
} | 97 |
# coding=utf-8
# Copyright 2024 HuggingFace Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ag... | diffusers/examples/consistency_distillation/test_lcm_lora.py/0 | {
"file_path": "diffusers/examples/consistency_distillation/test_lcm_lora.py",
"repo_id": "diffusers",
"token_count": 2105
} | 98 |
#!/usr/bin/env python
# coding=utf-8
# Copyright 2025 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LI... | diffusers/examples/controlnet/train_controlnet.py/0 | {
"file_path": "diffusers/examples/controlnet/train_controlnet.py",
"repo_id": "diffusers",
"token_count": 20524
} | 99 |
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