text stringlengths 7 328k | id stringlengths 14 166 | metadata dict | __index_level_0__ int64 0 459 |
|---|---|---|---|
from dataclasses import dataclass, field
from typing import List, Optional
from ..core import flatten_dict
@dataclass
class ModelConfig:
"""
Arguments which define the model and tokenizer to load.
"""
model_name_or_path: Optional[str] = field(
default=None,
metadata={"help": ("The mo... | trl/trl/trainer/model_config.py/0 | {
"file_path": "trl/trl/trainer/model_config.py",
"repo_id": "trl",
"token_count": 1309
} | 409 |
<!--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/launch.md/0 | {
"file_path": "accelerate/docs/source/basic_tutorials/launch.md",
"repo_id": "accelerate",
"token_count": 2702
} | 0 |
<!--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": 1156
} | 1 |
<!---
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 ... | accelerate/examples/README.md/0 | {
"file_path": "accelerate/examples/README.md",
"repo_id": "accelerate",
"token_count": 4466
} | 2 |
# Copyright 2021 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/cv_example.py/0 | {
"file_path": "accelerate/examples/cv_example.py",
"repo_id": "accelerate",
"token_count": 3205
} | 3 |
#!/bin/bash
#SBATCH --job-name=multinode
#SBATCH -D .
#SBATCH --output=O-%x.%j
#SBATCH --error=E-%x.%j
#SBATCH --nodes=4 # number of nodes
#SBATCH --ntasks-per-node=1 # number of MP tasks
#SBATCH --gres=gpu:4 # number of GPUs per node
#SBATCH --cpus-per-task=160 # numbe... | accelerate/examples/slurm/submit_multinode.sh/0 | {
"file_path": "accelerate/examples/slurm/submit_multinode.sh",
"repo_id": "accelerate",
"token_count": 519
} | 4 |
#!/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
} | 5 |
#!/usr/bin/env python
# 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
#
# Unles... | accelerate/src/accelerate/commands/tpu.py/0 | {
"file_path": "accelerate/src/accelerate/commands/tpu.py",
"repo_id": "accelerate",
"token_count": 2114
} | 6 |
# 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
#
# Unless required by appl... | accelerate/src/accelerate/test_utils/scripts/external_deps/test_checkpointing.py/0 | {
"file_path": "accelerate/src/accelerate/test_utils/scripts/external_deps/test_checkpointing.py",
"repo_id": "accelerate",
"token_count": 4189
} | 7 |
# 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/constants.py/0 | {
"file_path": "accelerate/src/accelerate/utils/constants.py",
"repo_id": "accelerate",
"token_count": 1126
} | 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/utils/tqdm.py/0 | {
"file_path": "accelerate/src/accelerate/utils/tqdm.py",
"repo_id": "accelerate",
"token_count": 433
} | 9 |
echo "hello world"
echo "this is a second command" | accelerate/tests/test_samples/test_command_file.sh/0 | {
"file_path": "accelerate/tests/test_samples/test_command_file.sh",
"repo_id": "accelerate",
"token_count": 14
} | 10 |
# Model arguments
model_name_or_path: bigcode/starcoder2-15b
model_revision: main
torch_dtype: bfloat16
use_flash_attention_2: true
# Data training arguments
chat_template: "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% for message in messages %}{{'<|im_start|>' + me... | alignment-handbook/recipes/starchat2-15b/sft/config_v0.1.yaml/0 | {
"file_path": "alignment-handbook/recipes/starchat2-15b/sft/config_v0.1.yaml",
"repo_id": "alignment-handbook",
"token_count": 565
} | 11 |
# coding=utf-8
# 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 requir... | alignment-handbook/src/alignment/configs.py/0 | {
"file_path": "alignment-handbook/src/alignment/configs.py",
"repo_id": "alignment-handbook",
"token_count": 4702
} | 12 |
repos:
- repo: https://github.com/Narsil/pre-commit-rust
rev: 2eed6366172ef2a5186e8785ec0e67243d7d73d0
hooks:
- id: fmt
name: "Rust (fmt)"
- id: clippy
name: "Rust (clippy)"
args:
[
"--tests",
"--examples",
"--",
"-D... | candle/.pre-commit-config.yaml/0 | {
"file_path": "candle/.pre-commit-config.yaml",
"repo_id": "candle",
"token_count": 210
} | 13 |
# Creating a REST api webserver
| candle/candle-book/src/apps/rest.md/0 | {
"file_path": "candle/candle-book/src/apps/rest.md",
"repo_id": "candle",
"token_count": 8
} | 14 |
//! #A simplified example in Rust of training a neural network and then using it based on the Candle Framework by Hugging Face.
//! Author: Evgeny Igumnov 2023 igumnovnsk@gmail.com
//! This program implements a neural network to predict the winner of the second round of elections based on the results of the first round... | candle/candle-book/src/simplified.rs/0 | {
"file_path": "candle/candle-book/src/simplified.rs",
"repo_id": "candle",
"token_count": 2903
} | 15 |
#[cfg(feature = "accelerate")]
extern crate accelerate_src;
#[cfg(feature = "mkl")]
extern crate intel_mkl_src;
use anyhow::Result;
use candle_core::{Device, Module, Tensor};
use candle_core::quantized::{QMatMul, QTensor};
fn main() -> Result<()> {
let device = Device::new_cuda(0)?;
let q = Tensor::randn(0f... | candle/candle-core/examples/cuda_basics.rs/0 | {
"file_path": "candle/candle-core/examples/cuda_basics.rs",
"repo_id": "candle",
"token_count": 550
} | 16 |
use crate::WithDType;
use cudarc;
use cudarc::cudnn::safe::{Conv2dForward, 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... | candle/candle-core/src/cudnn.rs/0 | {
"file_path": "candle/candle-core/src/cudnn.rs",
"repo_id": "candle",
"token_count": 2214
} | 17 |
use super::{GgmlDType, QStorage};
use crate::{backend::BackendDevice, cuda_backend::WrapErr};
use crate::{CudaDevice, CudaStorage, Result};
use cudarc::driver::{CudaSlice, DeviceSlice};
pub struct QCudaStorage {
data: CudaSlice<u8>,
dtype: GgmlDType,
device: CudaDevice,
}
pub const WARP_SIZE: usize = 32;... | candle/candle-core/src/quantized/cuda.rs/0 | {
"file_path": "candle/candle-core/src/quantized/cuda.rs",
"repo_id": "candle",
"token_count": 7006
} | 18 |
//! Tensors are N-dimensional matrixes of elements using a single data type.
#![allow(clippy::redundant_closure_call)]
use crate::backend::{BackendDevice, BackendStorage};
use crate::op::{
BackpropOp, BinaryOp, CmpOp, CustomOp1, CustomOp2, CustomOp3, Op, ReduceOp, UnaryOp,
};
use crate::scalar::TensorOrScalar;
use ... | candle/candle-core/src/tensor.rs/0 | {
"file_path": "candle/candle-core/src/tensor.rs",
"repo_id": "candle",
"token_count": 47594
} | 19 |
use candle_core::{
bail,
quantized::{self, GgmlDType},
test_device,
test_utils::to_vec2_round,
Device, Module, Result, Tensor,
};
use quantized::{k_quants, GgmlType};
use rand::prelude::*;
const GGML_TEST_SIZE: usize = 32 * 128;
const GGML_MAX_QUANTIZATION_TOTAL_ERROR: f32 = 0.002;
const GGML_MAX_... | candle/candle-core/tests/quantized_tests.rs/0 | {
"file_path": "candle/candle-core/tests/quantized_tests.rs",
"repo_id": "candle",
"token_count": 18159
} | 20 |
use candle::Tensor;
pub struct Dataset {
pub train_images: Tensor,
pub train_labels: Tensor,
pub test_images: Tensor,
pub test_labels: Tensor,
pub labels: usize,
}
pub mod cifar;
pub mod mnist;
| candle/candle-datasets/src/vision/mod.rs/0 | {
"file_path": "candle/candle-datasets/src/vision/mod.rs",
"repo_id": "candle",
"token_count": 92
} | 21 |
/*
* Adapted from
* https://github.com/NVIDIA/FasterTransformer/blob/release/v5.3_tag/src/fastertransformer/kernels/reduce_kernel_utils.cuh
* Copyright (c) 2023, The vLLM team.
* Copyright (c) 2020-2023, NVIDIA CORPORATION. All rights reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
... | candle/candle-examples/examples/custom-ops/kernels/reduction_utils.cuh/0 | {
"file_path": "candle/candle-examples/examples/custom-ops/kernels/reduction_utils.cuh",
"repo_id": "candle",
"token_count": 529
} | 22 |
# candle-metavoice
MetaVoice-1B is a text-to-speech model trained on 100K hours of speech, more
details on the [model
card](https://huggingface.co/metavoiceio/metavoice-1B-v0.1).
Note that the current candle implementation suffers from some limitations as of
2024-03-02:
- The speaker embeddings are hardcoded.
- The g... | candle/candle-examples/examples/metavoice/README.md/0 | {
"file_path": "candle/candle-examples/examples/metavoice/README.md",
"repo_id": "candle",
"token_count": 178
} | 23 |
# candle-quantized-t5
## Seq2Seq example
This example uses a quantized version of the t5 model.
```bash
$ cargo run --example quantized-t5 --release -- --prompt "translate to German: A beautiful candle."
...
Eine schöne Kerze.
```
## Generating Quantized weight files
The weight file is automatically retrieved fro... | candle/candle-examples/examples/quantized-t5/README.md/0 | {
"file_path": "candle/candle-examples/examples/quantized-t5/README.md",
"repo_id": "candle",
"token_count": 683
} | 24 |
# 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
} | 25 |
[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
} | 26 |
# candle-flash-attn
| candle/candle-flash-attn/README.md/0 | {
"file_path": "candle/candle-flash-attn/README.md",
"repo_id": "candle",
"token_count": 8
} | 27 |
use anyhow::Result;
use candle::{DType, Device, IndexOp, Tensor, D};
fn to_vec3_round(t: Tensor, digits: i32) -> Result<Vec<Vec<Vec<f32>>>> {
let b = 10f32.powi(digits);
let t = t.to_vec3::<f32>()?;
let t = t
.iter()
.map(|t| {
t.iter()
.map(|t| t.iter().map(|t| ... | candle/candle-flash-attn/tests/flash_attn_tests.rs/0 | {
"file_path": "candle/candle-flash-attn/tests/flash_attn_tests.rs",
"repo_id": "candle",
"token_count": 2787
} | 28 |
#include "cuda_utils.cuh"
#include<stdint.h>
#define WHERE_OP(TYPENAME, ID_TYPENAME, FN_NAME) \
extern "C" __global__ void FN_NAME( \
const size_t numel, \
const size_t num_dims, \
const size_t *info, \
const ID_TYPENAME *ids, \
const TYPENAME *t, \
const TYPENAME *f, \
TYPENAME *out \
) ... | candle/candle-kernels/src/ternary.cu/0 | {
"file_path": "candle/candle-kernels/src/ternary.cu",
"repo_id": "candle",
"token_count": 1159
} | 29 |
#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": 2340
} | 30 |
//! 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
} | 31 |
#[cfg(feature = "mkl")]
extern crate intel_mkl_src;
#[cfg(feature = "accelerate")]
extern crate accelerate_src;
use candle::{test_utils::to_vec3_round, Device, Result, Tensor};
#[test]
fn softmax() -> Result<()> {
let device = &Device::Cpu;
let data = &[[[3f32, 1., 4.], [1., 5., 9.]], [[2., 1., 7.], [8., 2.,... | candle/candle-nn/tests/ops.rs/0 | {
"file_path": "candle/candle-nn/tests/ops.rs",
"repo_id": "candle",
"token_count": 1170
} | 32 |
from candle.utils import load_safetensors, save_gguf, load_gguf
from candle.models.bert import BertModel, Config
import json
from candle import Tensor
from tqdm import tqdm
from dataclasses import fields
import os
import time
from huggingface_hub import hf_hub_download
from transformers import BertTokenizer, AutoModel... | candle/candle-pyo3/e5.py/0 | {
"file_path": "candle/candle-pyo3/e5.py",
"repo_id": "candle",
"token_count": 1778
} | 33 |
from typing import TypeVar, Union, Sequence
_T = TypeVar("_T")
_ArrayLike = Union[
_T,
Sequence[_T],
Sequence[Sequence[_T]],
Sequence[Sequence[Sequence[_T]]],
Sequence[Sequence[Sequence[Sequence[_T]]]],
]
CPU: str = "cpu"
CUDA: str = "cuda"
Device = TypeVar("Device", CPU, CUDA)
Scalar = Union[i... | candle/candle-pyo3/py_src/candle/typing/__init__.py/0 | {
"file_path": "candle/candle-pyo3/py_src/candle/typing/__init__.py",
"repo_id": "candle",
"token_count": 166
} | 34 |
from candle import Tensor
from candle import rand
import pytest
def test_absolute_shapes_are_valid():
a = rand((10, 20))
assert a.shape == (10, 20)
b = rand(10, 20)
assert b.shape == (10, 20)
pytest.raises(OverflowError, lambda: rand((10, 20, -1)))
pytest.raises(OverflowError, lambda: rand(-1... | candle/candle-pyo3/tests/native/test_shape.py/0 | {
"file_path": "candle/candle-pyo3/tests/native/test_shape.py",
"repo_id": "candle",
"token_count": 385
} | 35 |
use candle::{Result, Tensor, D};
use candle_nn as nn;
use nn::{Module, VarBuilder};
// Based on the Python version from torchvision.
// https://github.com/pytorch/vision/blob/0d75d9e5516f446c9c0ef93bd4ed9fea13992d06/torchvision/models/efficientnet.py#L47
#[derive(Debug, Clone, Copy)]
pub struct MBConvConfig {
expa... | candle/candle-transformers/src/models/efficientnet.rs/0 | {
"file_path": "candle/candle-transformers/src/models/efficientnet.rs",
"repo_id": "candle",
"token_count": 5123
} | 36 |
pub mod bert;
pub mod bigcode;
pub mod blip;
pub mod blip_text;
pub mod chatglm;
pub mod convmixer;
pub mod convnext;
pub mod dinov2;
pub mod distilbert;
pub mod efficientnet;
pub mod efficientvit;
pub mod encodec;
pub mod falcon;
pub mod gemma;
pub mod jina_bert;
pub mod llama;
pub mod llama2_c;
pub mod llama2_c_weigh... | candle/candle-transformers/src/models/mod.rs/0 | {
"file_path": "candle/candle-transformers/src/models/mod.rs",
"repo_id": "candle",
"token_count": 441
} | 37 |
use super::schedulers::{betas_for_alpha_bar, BetaSchedule, PredictionType};
use candle::{Result, Tensor};
#[derive(Debug, Clone, PartialEq, Eq)]
pub enum DDPMVarianceType {
FixedSmall,
FixedSmallLog,
FixedLarge,
FixedLargeLog,
Learned,
}
impl Default for DDPMVarianceType {
fn default() -> Self... | candle/candle-transformers/src/models/stable_diffusion/ddpm.rs/0 | {
"file_path": "candle/candle-transformers/src/models/stable_diffusion/ddpm.rs",
"repo_id": "candle",
"token_count": 3662
} | 38 |
// Audio processing code, adapted from whisper.cpp
// https://github.com/ggerganov/whisper.cpp
use candle::utils::get_num_threads;
use std::sync::Arc;
use std::thread;
pub trait Float:
num_traits::Float + num_traits::FloatConst + num_traits::NumAssign + Send + Sync
{
}
impl Float for f32 {}
impl Float for f64 {}... | candle/candle-transformers/src/models/whisper/audio.rs/0 | {
"file_path": "candle/candle-transformers/src/models/whisper/audio.rs",
"repo_id": "candle",
"token_count": 5282
} | 39 |
use crate::models::with_tracing::QMatMul;
use crate::quantized_var_builder::VarBuilder;
use candle::{Module, Result, Tensor};
#[derive(Debug, Clone)]
pub struct Embedding {
inner: candle_nn::Embedding,
span: tracing::Span,
}
impl Embedding {
pub fn new(d1: usize, d2: usize, vb: VarBuilder) -> Result<Self>... | candle/candle-transformers/src/quantized_nn.rs/0 | {
"file_path": "candle/candle-transformers/src/quantized_nn.rs",
"repo_id": "candle",
"token_count": 1534
} | 40 |
<!DOCTYPE html>
<html>
<head>
<meta charset="UTF-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<style>
@import url("https://fonts.googleapis.com/css2?family=Source+Code+Pro:wght@200;300;400&family=Source+Sans+3:wght@100;200;300;400;500;600;700;800;900&display=swap");... | candle/candle-wasm-examples/blip/index.html/0 | {
"file_path": "candle/candle-wasm-examples/blip/index.html",
"repo_id": "candle",
"token_count": 7164
} | 41 |
use crate::model::{Cache, Config, Llama};
use byteorder::{LittleEndian, ReadBytesExt};
use candle::{DType, Device, IndexOp, Result, Shape, Tensor};
use candle_nn::VarBuilder;
use candle_transformers::generation::LogitsProcessor;
use serde::{Deserialize, Serialize};
use tokenizers::Tokenizer;
use wasm_bindgen::prelude::... | candle/candle-wasm-examples/llama2-c/src/worker.rs/0 | {
"file_path": "candle/candle-wasm-examples/llama2-c/src/worker.rs",
"repo_id": "candle",
"token_count": 5770
} | 42 |
// Audio processing code, adapted from whisper.cpp
// https://github.com/ggerganov/whisper.cpp
use super::worker;
pub trait Float: num_traits::Float + num_traits::FloatConst + num_traits::NumAssign {}
impl Float for f32 {}
impl Float for f64 {}
// https://github.com/ggerganov/whisper.cpp/blob/4774d2feb01a772a15de81f... | candle/candle-wasm-examples/whisper/src/audio.rs/0 | {
"file_path": "candle/candle-wasm-examples/whisper/src/audio.rs",
"repo_id": "candle",
"token_count": 3162
} | 43 |
use yew_agent::PublicWorker;
fn main() {
console_error_panic_hook::set_once();
candle_wasm_example_yolo::Worker::register();
}
| candle/candle-wasm-examples/yolo/src/bin/worker.rs/0 | {
"file_path": "candle/candle-wasm-examples/yolo/src/bin/worker.rs",
"repo_id": "candle",
"token_count": 53
} | 44 |
.DS_Store
node_modules
/build
/.svelte-kit
/package
.env
.env.*
!.env.example
# Ignore files for PNPM, NPM and YARN
pnpm-lock.yaml
package-lock.json
yarn.lock
| chat-ui/.eslintignore/0 | {
"file_path": "chat-ui/.eslintignore",
"repo_id": "chat-ui",
"token_count": 69
} | 45 |
import fs from "fs";
const SECRET_CONFIG = fs.existsSync(".env.SECRET_CONFIG")
? fs.readFileSync(".env.SECRET_CONFIG", "utf8")
: process.env.SECRET_CONFIG;
if (!SECRET_CONFIG) {
throw new Error(
"SECRET_CONFIG is not defined. Please provide it either in a file or as an environment variable."
);
}
// Read the c... | chat-ui/scripts/updateLocalEnv.ts/0 | {
"file_path": "chat-ui/scripts/updateLocalEnv.ts",
"repo_id": "chat-ui",
"token_count": 217
} | 46 |
<script lang="ts">
import { base } from "$app/paths";
import { page } from "$app/stores";
import { PUBLIC_APP_DESCRIPTION, PUBLIC_APP_NAME } from "$env/static/public";
import LogoHuggingFaceBorderless from "$lib/components/icons/LogoHuggingFaceBorderless.svelte";
import Modal from "$lib/components/Modal.svelte";
... | chat-ui/src/lib/components/LoginModal.svelte/0 | {
"file_path": "chat-ui/src/lib/components/LoginModal.svelte",
"repo_id": "chat-ui",
"token_count": 917
} | 47 |
<script lang="ts">
export let classNames = "";
export let label = "Copied";
export let position = "left-1/2 top-full transform -translate-x-1/2 translate-y-2";
</script>
<div
class="
pointer-events-none absolute rounded bg-black px-2 py-1 font-normal leading-tight text-white shadow transition-opacity
{position... | chat-ui/src/lib/components/Tooltip.svelte/0 | {
"file_path": "chat-ui/src/lib/components/Tooltip.svelte",
"repo_id": "chat-ui",
"token_count": 216
} | 48 |
import { buildPrompt } from "$lib/buildPrompt";
import { textGenerationStream } from "@huggingface/inference";
import { z } from "zod";
import type { Endpoint } from "../endpoints";
export const endpointAwsParametersSchema = z.object({
weight: z.number().int().positive().default(1),
model: z.any(),
type: z.literal(... | chat-ui/src/lib/server/endpoints/aws/endpointAws.ts/0 | {
"file_path": "chat-ui/src/lib/server/endpoints/aws/endpointAws.ts",
"repo_id": "chat-ui",
"token_count": 558
} | 49 |
import { LLM_SUMMERIZATION } from "$env/static/private";
import { generateFromDefaultEndpoint } from "$lib/server/generateFromDefaultEndpoint";
import type { Message } from "$lib/types/Message";
export async function summarize(prompt: string) {
if (!LLM_SUMMERIZATION) {
return prompt.split(/\s+/g).slice(0, 5).join(... | chat-ui/src/lib/server/summarize.ts/0 | {
"file_path": "chat-ui/src/lib/server/summarize.ts",
"repo_id": "chat-ui",
"token_count": 638
} | 50 |
export function switchTheme() {
const { classList } = document.querySelector("html") as HTMLElement;
const metaTheme = document.querySelector('meta[name="theme-color"]') as HTMLMetaElement;
if (classList.contains("dark")) {
classList.remove("dark");
metaTheme.setAttribute("content", "rgb(249, 250, 251)");
loc... | chat-ui/src/lib/switchTheme.ts/0 | {
"file_path": "chat-ui/src/lib/switchTheme.ts",
"repo_id": "chat-ui",
"token_count": 164
} | 51 |
import type { Message } from "./Message";
export type LegacyParamatersTemplateInput = {
preprompt?: string;
userMessageToken: string;
userMessageEndToken: string;
assistantMessageToken: string;
assistantMessageEndToken: string;
};
export type ChatTemplateInput = {
messages: Pick<Message, "from" | "content">[];
... | chat-ui/src/lib/types/Template.ts/0 | {
"file_path": "chat-ui/src/lib/types/Template.ts",
"repo_id": "chat-ui",
"token_count": 105
} | 52 |
// Approximate width from which we disable autofocus
const TABLET_VIEWPORT_WIDTH = 768;
export function isDesktop(window: Window) {
const { innerWidth } = window;
return innerWidth > TABLET_VIEWPORT_WIDTH;
}
| chat-ui/src/lib/utils/isDesktop.ts/0 | {
"file_path": "chat-ui/src/lib/utils/isDesktop.ts",
"repo_id": "chat-ui",
"token_count": 67
} | 53 |
import type { Conversation } from "$lib/types/Conversation";
import type { Message } from "$lib/types/Message";
import { v4 } from "uuid";
export function addSibling(
conv: Pick<Conversation, "messages" | "rootMessageId">,
message: Omit<Message, "id">,
siblingId: Message["id"]
): Message["id"] {
if (conv.messages.... | chat-ui/src/lib/utils/tree/addSibling.ts/0 | {
"file_path": "chat-ui/src/lib/utils/tree/addSibling.ts",
"repo_id": "chat-ui",
"token_count": 439
} | 54 |
import { models } from "$lib/server/models";
export async function GET() {
const res = models.map((model) => ({
id: model.id,
name: model.name,
websiteUrl: model.websiteUrl,
modelUrl: model.modelUrl,
datasetName: model.datasetName,
datasetUrl: model.datasetUrl,
displayName: model.displayName,
descript... | chat-ui/src/routes/api/models/+server.ts/0 | {
"file_path": "chat-ui/src/routes/api/models/+server.ts",
"repo_id": "chat-ui",
"token_count": 206
} | 55 |
import { authCondition } from "$lib/server/auth";
import { collections } from "$lib/server/database";
import { error } from "@sveltejs/kit";
import { ObjectId } from "mongodb";
/**
* Ideally, we'd be able to detect the client-side abort, see https://github.com/huggingface/chat-ui/pull/88#issuecomment-1523173850
*/
e... | chat-ui/src/routes/conversation/[id]/stop-generating/+server.ts/0 | {
"file_path": "chat-ui/src/routes/conversation/[id]/stop-generating/+server.ts",
"repo_id": "chat-ui",
"token_count": 261
} | 56 |
import { collections } from "$lib/server/database";
import { z } from "zod";
import { authCondition } from "$lib/server/auth";
import { DEFAULT_SETTINGS } from "$lib/types/Settings";
export async function POST({ request, locals }) {
const body = await request.json();
const { ethicsModalAccepted, ...settings } = z
... | chat-ui/src/routes/settings/(nav)/+server.ts/0 | {
"file_path": "chat-ui/src/routes/settings/(nav)/+server.ts",
"repo_id": "chat-ui",
"token_count": 401
} | 57 |
import { sveltekit } from "@sveltejs/kit/vite";
import { defineConfig, type PluginOption } from "vite";
import Icons from "unplugin-icons/vite";
import { promises } from "fs";
// used to load fonts server side for thumbnail generation
function loadTTFAsArrayBuffer(): PluginOption {
return {
name: "load-ttf-as-array... | chat-ui/vite.config.ts/0 | {
"file_path": "chat-ui/vite.config.ts",
"repo_id": "chat-ui",
"token_count": 276
} | 58 |
{
"license": "Apache-2.0",
"creators": [
{
"affiliation": "Hugging Face",
"name": "Quentin Lhoest"
},
{
"orcid": "0000-0003-1727-1045",
"affiliation": "Hugging Face",
"name": "Albert Villanova del Moral"
},
{
... | datasets/.zenodo.json/0 | {
"file_path": "datasets/.zenodo.json",
"repo_id": "datasets",
"token_count": 1953
} | 59 |
import json
import sys
def format_json_to_md(input_json_file, output_md_file):
with open(input_json_file, encoding="utf-8") as f:
results = json.load(f)
output_md = ["<details>", "<summary>Show updated benchmarks!</summary>", " "]
for benchmark_name in sorted(results):
benchmark_res = re... | datasets/benchmarks/format.py/0 | {
"file_path": "datasets/benchmarks/format.py",
"repo_id": "datasets",
"token_count": 746
} | 60 |
# Batch mapping
Combining the utility of [`Dataset.map`] with batch mode is very powerful. It allows you to speed up processing, and freely control the size of the generated dataset.
## Need for speed
The primary objective of batch mapping is to speed up processing. Often times, it is faster to work with batches of... | datasets/docs/source/about_map_batch.mdx/0 | {
"file_path": "datasets/docs/source/about_map_batch.mdx",
"repo_id": "datasets",
"token_count": 722
} | 61 |
# Metrics
<Tip warning={true}>
Metrics is deprecated in 🤗 Datasets. To learn more about how to use metrics, take a look at the library 🤗 [Evaluate](https://huggingface.co/docs/evaluate/index)! In addition to metrics, you can find more tools for evaluating models and datasets.
</Tip>
Metrics are important for eval... | datasets/docs/source/how_to_metrics.mdx/0 | {
"file_path": "datasets/docs/source/how_to_metrics.mdx",
"repo_id": "datasets",
"token_count": 3350
} | 62 |
# Loading methods
Methods for listing and loading datasets and metrics:
## Datasets
[[autodoc]] datasets.list_datasets
[[autodoc]] datasets.load_dataset
[[autodoc]] datasets.load_from_disk
[[autodoc]] datasets.load_dataset_builder
[[autodoc]] datasets.get_dataset_config_names
[[autodoc]] datasets.get_dataset_in... | datasets/docs/source/package_reference/loading_methods.mdx/0 | {
"file_path": "datasets/docs/source/package_reference/loading_methods.mdx",
"repo_id": "datasets",
"token_count": 809
} | 63 |
# Use with JAX
This document is a quick introduction to using `datasets` with JAX, with a particular focus on how to get
`jax.Array` objects out of our datasets, and how to use them to train JAX models.
<Tip>
`jax` and `jaxlib` are required to reproduce to code above, so please make sure you
install them as `pip ins... | datasets/docs/source/use_with_jax.mdx/0 | {
"file_path": "datasets/docs/source/use_with_jax.mdx",
"repo_id": "datasets",
"token_count": 2646
} | 64 |
# Copyright 2021 The HuggingFace 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
#
# Unless required by applicable law or ... | datasets/metrics/chrf/chrf.py/0 | {
"file_path": "datasets/metrics/chrf/chrf.py",
"repo_id": "datasets",
"token_count": 3170
} | 65 |
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# 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.... | datasets/metrics/f1/f1.py/0 | {
"file_path": "datasets/metrics/f1/f1.py",
"repo_id": "datasets",
"token_count": 2364
} | 66 |
# coding=utf-8
# Copyright 2020 The HuggingFace 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
#
# Unless required by app... | datasets/metrics/mauve/mauve.py/0 | {
"file_path": "datasets/metrics/mauve/mauve.py",
"repo_id": "datasets",
"token_count": 2588
} | 67 |
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# 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.... | datasets/metrics/roc_auc/roc_auc.py/0 | {
"file_path": "datasets/metrics/roc_auc/roc_auc.py",
"repo_id": "datasets",
"token_count": 3792
} | 68 |
# Copyright 2020 The HuggingFace 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
#
# Unless required by applicable law or ... | datasets/metrics/squad_v2/squad_v2.py/0 | {
"file_path": "datasets/metrics/squad_v2/squad_v2.py",
"repo_id": "datasets",
"token_count": 2564
} | 69 |
[tool.ruff]
line-length = 119
[tool.ruff.lint]
# Ignored rules:
# "E501" -> line length violation
# "F821" -> undefined named in type annotation (e.g. Literal["something"])
# "C901" -> `function_name` is too complex
ignore = ["E501", "F821", "C901"]
select = ["C", "E", "F", "I", "W"]
[tool.ruff.lint.isort]
line... | datasets/pyproject.toml/0 | {
"file_path": "datasets/pyproject.toml",
"repo_id": "datasets",
"token_count": 236
} | 70 |
import os
import re
from functools import partial
from glob import has_magic
from pathlib import Path, PurePath
from typing import Callable, Dict, List, Optional, Set, Tuple, Union
import huggingface_hub
from fsspec.core import url_to_fs
from fsspec.implementations.http import HTTPFileSystem
from huggingface_hub impor... | datasets/src/datasets/data_files.py/0 | {
"file_path": "datasets/src/datasets/data_files.py",
"repo_id": "datasets",
"token_count": 13855
} | 71 |
import s3fs
from ..utils.deprecation_utils import deprecated
@deprecated("Use s3fs.S3FileSystem instead.")
class S3FileSystem(s3fs.S3FileSystem):
"""
`datasets.filesystems.S3FileSystem` is a subclass of [`s3fs.S3FileSystem`](https://s3fs.readthedocs.io/en/latest/api.html).
Users can use this class to ac... | datasets/src/datasets/filesystems/s3filesystem.py/0 | {
"file_path": "datasets/src/datasets/filesystems/s3filesystem.py",
"repo_id": "datasets",
"token_count": 2170
} | 72 |
import os
from typing import BinaryIO, Optional, Union
import fsspec
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_modules import _PACKAG... | datasets/src/datasets/io/parquet.py/0 | {
"file_path": "datasets/src/datasets/io/parquet.py",
"repo_id": "datasets",
"token_count": 2585
} | 73 |
import abc
import copy
import dataclasses
from dataclasses import dataclass
from typing import ClassVar, Dict, Type, TypeVar
from ..features import Features
T = TypeVar("T", bound="TaskTemplate")
@dataclass(frozen=True)
class TaskTemplate(abc.ABC):
# `task` is not a ClassVar since we want it to be part of the ... | datasets/src/datasets/tasks/base.py/0 | {
"file_path": "datasets/src/datasets/tasks/base.py",
"repo_id": "datasets",
"token_count": 417
} | 74 |
"""
Utilities for working with the local dataset cache.
This file is adapted from the AllenNLP library at https://github.com/allenai/allennlp
Copyright by the AllenNLP authors.
"""
import copy
import io
import json
import multiprocessing
import os
import posixpath
import re
import shutil
import sys
import time
import ... | datasets/src/datasets/utils/file_utils.py/0 | {
"file_path": "datasets/src/datasets/utils/file_utils.py",
"repo_id": "datasets",
"token_count": 11061
} | 75 |
import numpy as np
def approximate_mode(class_counts, n_draws, rng):
"""Computes approximate mode of multivariate hypergeometric.
This is an approximation to the mode of the multivariate
hypergeometric given by class_counts and n_draws.
It shouldn't be off by more than one.
It is the mostly likely... | datasets/src/datasets/utils/stratify.py/0 | {
"file_path": "datasets/src/datasets/utils/stratify.py",
"repo_id": "datasets",
"token_count": 1674
} | 76 |
import pytest
import datasets
import datasets.config
# Import fixture modules as plugins
pytest_plugins = ["tests.fixtures.files", "tests.fixtures.hub", "tests.fixtures.fsspec"]
def pytest_collection_modifyitems(config, items):
# Mark tests as "unit" by default if not marked as "integration" (or already marked... | datasets/tests/conftest.py/0 | {
"file_path": "datasets/tests/conftest.py",
"repo_id": "datasets",
"token_count": 957
} | 77 |
import posixpath
from pathlib import Path
from unittest.mock import patch
import pytest
from fsspec.implementations.local import AbstractFileSystem, LocalFileSystem, stringify_path
from fsspec.registry import _registry as _fsspec_registry
class MockFileSystem(AbstractFileSystem):
protocol = "mock"
def __ini... | datasets/tests/fixtures/fsspec.py/0 | {
"file_path": "datasets/tests/fixtures/fsspec.py",
"repo_id": "datasets",
"token_count": 1757
} | 78 |
import shutil
import textwrap
import numpy as np
import pytest
from datasets import ClassLabel, Features, Image, Value
from datasets.data_files import DataFilesDict, get_data_patterns
from datasets.download.streaming_download_manager import StreamingDownloadManager
from datasets.packaged_modules.imagefolder.imagefold... | datasets/tests/packaged_modules/test_imagefolder.py/0 | {
"file_path": "datasets/tests/packaged_modules/test_imagefolder.py",
"repo_id": "datasets",
"token_count": 8692
} | 79 |
import os
import zipfile
import pytest
from datasets.utils.extract import (
Bzip2Extractor,
Extractor,
GzipExtractor,
Lz4Extractor,
SevenZipExtractor,
TarExtractor,
XzExtractor,
ZipExtractor,
ZstdExtractor,
)
from .utils import require_lz4, require_py7zr, require_zstandard
@pyte... | datasets/tests/test_extract.py/0 | {
"file_path": "datasets/tests/test_extract.py",
"repo_id": "datasets",
"token_count": 2984
} | 80 |
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def test_offline_with_timeout():
with offline(OfflineSimulationMode.CONNECTION_TIMES_OUT):
with pytest.raises(Reques... | datasets/tests/test_offline_util.py/0 | {
"file_path": "datasets/tests/test_offline_util.py",
"repo_id": "datasets",
"token_count": 382
} | 81 |
<jupyter_start><jupyter_text>Unit 8 Part 2: Advanced Deep Reinforcement Learning. Using Sample Factory to play Doom from pixelsIn this notebook, we will learn how to train a Deep Neural Network to collect objects in a 3D environment based on the game of Doom, a video of the resulting policy is shown below. We train thi... | deep-rl-class/notebooks/unit8/unit8_part2.ipynb/0 | {
"file_path": "deep-rl-class/notebooks/unit8/unit8_part2.ipynb",
"repo_id": "deep-rl-class",
"token_count": 4950
} | 82 |
# The Reinforcement Learning Framework [[the-reinforcement-learning-framework]]
## The RL Process [[the-rl-process]]
<figure>
<img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit1/RL_process.jpg" alt="The RL process" width="100%">
<figcaption>The RL Process: a loop o... | deep-rl-class/units/en/unit1/rl-framework.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit1/rl-framework.mdx",
"repo_id": "deep-rl-class",
"token_count": 2504
} | 83 |
# Introducing Q-Learning [[q-learning]]
## What is Q-Learning? [[what-is-q-learning]]
Q-Learning is an **off-policy value-based method that uses a TD approach to train its action-value function:**
- *Off-policy*: we'll talk about that at the end of this unit.
- *Value-based method*: finds the optimal policy indirectl... | deep-rl-class/units/en/unit2/q-learning.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit2/q-learning.mdx",
"repo_id": "deep-rl-class",
"token_count": 2955
} | 84 |
# Glossary
This is a community-created glossary. Contributions are welcome!
- **Deep Q-Learning:** A value-based deep reinforcement learning algorithm that uses a deep neural network to approximate Q-values for actions in a given state. The goal of Deep Q-learning is to find the optimal policy that maximizes the exp... | deep-rl-class/units/en/unit4/glossary.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit4/glossary.mdx",
"repo_id": "deep-rl-class",
"token_count": 421
} | 85 |
# Additional Readings [[additional-readings]]
## Bias-variance tradeoff in Reinforcement Learning
If you want to dive deeper into the question of variance and bias tradeoff in Deep Reinforcement Learning, you can check out these two articles:
- [Making Sense of the Bias / Variance Trade-off in (Deep) Reinforcement L... | deep-rl-class/units/en/unit6/additional-readings.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit6/additional-readings.mdx",
"repo_id": "deep-rl-class",
"token_count": 321
} | 86 |
# Introducing the Clipped Surrogate Objective Function
## Recap: The Policy Objective Function
Let’s remember what the objective is to optimize in Reinforce:
<img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit9/lpg.jpg" alt="Reinforce"/>
The idea was that by taking ... | deep-rl-class/units/en/unit8/clipped-surrogate-objective.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit8/clipped-surrogate-objective.mdx",
"repo_id": "deep-rl-class",
"token_count": 1386
} | 87 |
# Optuna Tutorial [[optuna]]
The content below comes from [Antonin's Raffin ICRA 2022 presentations](https://araffin.github.io/tools-for-robotic-rl-icra2022/), he's one of the founders of Stable-Baselines and RL-Baselines3-Zoo.
## The theory behind Hyperparameter tuning
<Youtube id="AidFTOdGNFQ" />
## Optuna Tuto... | deep-rl-class/units/en/unitbonus2/optuna.mdx/0 | {
"file_path": "deep-rl-class/units/en/unitbonus2/optuna.mdx",
"repo_id": "deep-rl-class",
"token_count": 182
} | 88 |
import argparse
import sys
sys.path.append(".")
from base_classes import ImageToImageBenchmark, TurboImageToImageBenchmark # noqa: E402
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument(
"--ckpt",
type=str,
default="runwayml/stable-diffusion-v1-5",
... | diffusers/benchmarks/benchmark_sd_img.py/0 | {
"file_path": "diffusers/benchmarks/benchmark_sd_img.py",
"repo_id": "diffusers",
"token_count": 415
} | 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... | diffusers/docs/README.md/0 | {
"file_path": "diffusers/docs/README.md",
"repo_id": "diffusers",
"token_count": 3145
} | 90 |
<!--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/pndm.md/0 | {
"file_path": "diffusers/docs/source/en/api/schedulers/pndm.md",
"repo_id": "diffusers",
"token_count": 304
} | 91 |
<!--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/index.md/0 | {
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"repo_id": "diffusers",
"token_count": 1316
} | 92 |
# Adapt a model to a new task
Many diffusion systems share the same components, allowing you to adapt a pretrained model for one task to an entirely different task.
This guide will show you how to adapt a pretrained text-to-image model for inpainting by initializing and modifying the architecture of a pretrained [`UN... | diffusers/docs/source/en/training/adapt_a_model.md/0 | {
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"repo_id": "diffusers",
"token_count": 779
} | 93 |
<!--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/unconditional_training.md/0 | {
"file_path": "diffusers/docs/source/en/training/unconditional_training.md",
"repo_id": "diffusers",
"token_count": 2949
} | 94 |
<!--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/diffedit.md/0 | {
"file_path": "diffusers/docs/source/en/using-diffusers/diffedit.md",
"repo_id": "diffusers",
"token_count": 3847
} | 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 applicable law or agreed... | diffusers/docs/source/en/using-diffusers/pipeline_overview.md/0 | {
"file_path": "diffusers/docs/source/en/using-diffusers/pipeline_overview.md",
"repo_id": "diffusers",
"token_count": 327
} | 96 |
- sections:
- local: index
title: 🧨 Diffusers
- local: quicktour
title: クイックツアー
- local: stable_diffusion
title: 有効で効率の良い拡散モデル
- local: installation
title: インストール
title: はじめに
- sections:
- local: tutorials/tutorial_overview
title: 概要
- local: tutorials/autopipeline
title: AutoPipe... | diffusers/docs/source/ja/_toctree.yml/0 | {
"file_path": "diffusers/docs/source/ja/_toctree.yml",
"repo_id": "diffusers",
"token_count": 166
} | 97 |
<!--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/optimization/onnx.md/0 | {
"file_path": "diffusers/docs/source/ko/optimization/onnx.md",
"repo_id": "diffusers",
"token_count": 1437
} | 98 |
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