text stringlengths 7 318k | id stringlengths 14 166 | metadata dict | __index_level_0__ int64 0 439 |
|---|---|---|---|
#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
} | 27 |
#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": 1890
} | 28 |
//! 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
} | 29 |
#[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
} | 30 |
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
} | 31 |
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
} | 32 |
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
} | 33 |
use super::with_tracing::{linear, linear_no_bias, Embedding, Linear};
use candle::{DType, Device, IndexOp, Result, Tensor, D};
use candle_nn::{layer_norm, LayerNorm, Module, VarBuilder};
use serde::Deserialize;
pub const DTYPE: DType = DType::F32;
#[derive(Debug, Clone, Copy, PartialEq, Eq, Deserialize)]
#[serde(rena... | candle/candle-transformers/src/models/jina_bert.rs/0 | {
"file_path": "candle/candle-transformers/src/models/jina_bert.rs",
"repo_id": "candle",
"token_count": 5806
} | 34 |
use super::llama2_c::{Cache, Config};
use crate::quantized_nn::{linear_no_bias as linear, Embedding, Linear, RmsNorm};
pub use crate::quantized_var_builder::VarBuilder;
use candle::{DType, IndexOp, Module, Result, Tensor, D};
fn silu(xs: &Tensor) -> Result<Tensor> {
xs / (xs.neg()?.exp()? + 1.0)?
}
struct CausalS... | candle/candle-transformers/src/models/quantized_llama2_c.rs/0 | {
"file_path": "candle/candle-transformers/src/models/quantized_llama2_c.rs",
"repo_id": "candle",
"token_count": 4287
} | 35 |
//! Contrastive Language-Image Pre-Training
//!
//! Contrastive Language-Image Pre-Training (CLIP) is an architecture trained on
//! pairs of images with related texts.
//!
//! https://github.com/openai/CLIP
use candle::{DType, Device, Result, Tensor, D};
use candle_nn as nn;
use candle_nn::Module;
#[derive(Debug, Clo... | candle/candle-transformers/src/models/stable_diffusion/clip.rs/0 | {
"file_path": "candle/candle-transformers/src/models/stable_diffusion/clip.rs",
"repo_id": "candle",
"token_count": 6474
} | 36 |
#![allow(unused)]
use crate::models::with_tracing::{conv2d, linear, linear_no_bias, Conv2d, Linear};
use candle::{IndexOp, Module, Result, Tensor, D};
use candle_nn::{layer_norm, LayerNorm, VarBuilder};
// https://github.com/huggingface/transformers/blob/main/src/transformers/models/vit/configuration_vit.py
#[derive(D... | candle/candle-transformers/src/models/vit.rs/0 | {
"file_path": "candle/candle-transformers/src/models/vit.rs",
"repo_id": "candle",
"token_count": 5820
} | 37 |
use candle::{DType, Device, IndexOp, Result, Tensor, D};
use candle_nn::{
embedding, linear_no_bias as linear, rms_norm, Embedding, Linear, Module, RmsNorm, VarBuilder,
};
use std::collections::HashMap;
use std::sync::{Arc, Mutex};
#[derive(Debug, Clone)]
pub struct Config {
pub dim: usize, // transform... | candle/candle-wasm-examples/llama2-c/src/model.rs/0 | {
"file_path": "candle/candle-wasm-examples/llama2-c/src/model.rs",
"repo_id": "candle",
"token_count": 5272
} | 38 |
[package]
name = "candle-wasm-example-t5"
version.workspace = true
edition.workspace = true
description.workspace = true
repository.workspace = true
keywords.workspace = true
categories.workspace = true
license.workspace = true
[dependencies]
candle = { workspace = true }
candle-nn = { workspace = true }
candle-transf... | candle/candle-wasm-examples/t5/Cargo.toml/0 | {
"file_path": "candle/candle-wasm-examples/t5/Cargo.toml",
"repo_id": "candle",
"token_count": 305
} | 39 |
use crate::console_log;
use crate::worker::{ModelData, Segment, Worker, WorkerInput, WorkerOutput};
use js_sys::Date;
use wasm_bindgen::prelude::*;
use wasm_bindgen_futures::JsFuture;
use yew::{html, Component, Context, Html};
use yew_agent::{Bridge, Bridged};
const SAMPLE_NAMES: [&str; 6] = [
"audios/samples_jfk.... | candle/candle-wasm-examples/whisper/src/app.rs/0 | {
"file_path": "candle/candle-wasm-examples/whisper/src/app.rs",
"repo_id": "candle",
"token_count": 5679
} | 40 |
use candle_wasm_example_yolo::coco_classes;
use candle_wasm_example_yolo::model::Bbox;
use candle_wasm_example_yolo::worker::Model as M;
use candle_wasm_example_yolo::worker::ModelPose as P;
use wasm_bindgen::prelude::*;
#[wasm_bindgen]
pub struct Model {
inner: M,
}
#[wasm_bindgen]
impl Model {
#[wasm_bindge... | candle/candle-wasm-examples/yolo/src/bin/m.rs/0 | {
"file_path": "candle/candle-wasm-examples/yolo/src/bin/m.rs",
"repo_id": "candle",
"token_count": 840
} | 41 |
# template used in production for HuggingChat.
MODELS=`[
{
"name" : "mistralai/Mixtral-8x7B-Instruct-v0.1",
"description" : "The latest MoE model from Mistral AI! 8x7B and outperforms Llama 2 70B in most benchmarks.",
"websiteUrl" : "https://mistral.ai/news/mixtral-of-experts/",
"preprompt" : "",
... | chat-ui/.env.template/0 | {
"file_path": "chat-ui/.env.template",
"repo_id": "chat-ui",
"token_count": 4655
} | 42 |
import fs from "fs";
const HF_DEPLOYMENT_TOKEN = process.env.HF_DEPLOYMENT_TOKEN; // token used for pushing to hub
const SERPER_API_KEY = process.env.SERPER_API_KEY;
const OPENID_CONFIG = process.env.OPENID_CONFIG;
const MONGODB_URL = process.env.MONGODB_URL;
const HF_TOKEN = process.env.HF_TOKEN ?? process.env.HF_AC... | chat-ui/scripts/updateProdEnv.ts/0 | {
"file_path": "chat-ui/scripts/updateProdEnv.ts",
"repo_id": "chat-ui",
"token_count": 423
} | 43 |
<script lang="ts">
import { createEventDispatcher, onDestroy, onMount } from "svelte";
import { cubicOut } from "svelte/easing";
import { fade } from "svelte/transition";
import Portal from "./Portal.svelte";
import { browser } from "$app/environment";
export let width = "max-w-sm";
let backdropEl: HTMLDivElem... | chat-ui/src/lib/components/Modal.svelte/0 | {
"file_path": "chat-ui/src/lib/components/Modal.svelte",
"repo_id": "chat-ui",
"token_count": 642
} | 44 |
<script lang="ts">
import { createEventDispatcher, onMount } from "svelte";
export let value = "";
export let minRows = 1;
export let maxRows: null | number = null;
export let placeholder = "";
export let disabled = false;
// Approximate width from which we disable autofocus
const TABLET_VIEWPORT_WIDTH = 768;
... | chat-ui/src/lib/components/chat/ChatInput.svelte/0 | {
"file_path": "chat-ui/src/lib/components/chat/ChatInput.svelte",
"repo_id": "chat-ui",
"token_count": 663
} | 45 |
import { Issuer, BaseClient, type UserinfoResponse, TokenSet, custom } from "openid-client";
import { addHours, addWeeks } from "date-fns";
import {
COOKIE_NAME,
OPENID_CLIENT_ID,
OPENID_CLIENT_SECRET,
OPENID_PROVIDER_URL,
OPENID_SCOPES,
OPENID_TOLERANCE,
OPENID_RESOURCE,
OPENID_CONFIG,
} from "$env/static/priv... | chat-ui/src/lib/server/auth.ts/0 | {
"file_path": "chat-ui/src/lib/server/auth.ts",
"repo_id": "chat-ui",
"token_count": 1500
} | 46 |
import { smallModel } from "$lib/server/models";
import type { Conversation } from "$lib/types/Conversation";
export async function generateFromDefaultEndpoint({
messages,
preprompt,
}: {
messages: Omit<Conversation["messages"][0], "id">[];
preprompt?: string;
}): Promise<string> {
const endpoint = await smallMod... | chat-ui/src/lib/server/generateFromDefaultEndpoint.ts/0 | {
"file_path": "chat-ui/src/lib/server/generateFromDefaultEndpoint.ts",
"repo_id": "chat-ui",
"token_count": 293
} | 47 |
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
} | 48 |
import type { ObjectId } from "mongodb";
import type { Timestamps } from "./Timestamps";
export interface User extends Timestamps {
_id: ObjectId;
username?: string;
name: string;
email?: string;
avatarUrl: string;
hfUserId: string;
}
| chat-ui/src/lib/types/User.ts/0 | {
"file_path": "chat-ui/src/lib/types/User.ts",
"repo_id": "chat-ui",
"token_count": 83
} | 49 |
// https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Statements/for-await...of#iterating_over_async_generators
export async function* streamToAsyncIterable(
stream: ReadableStream<Uint8Array>
): AsyncIterableIterator<Uint8Array> {
const reader = stream.getReader();
try {
while (true) {
const { d... | chat-ui/src/lib/utils/streamToAsyncIterable.ts/0 | {
"file_path": "chat-ui/src/lib/utils/streamToAsyncIterable.ts",
"repo_id": "chat-ui",
"token_count": 161
} | 50 |
<script lang="ts">
export let name: string;
export let description: string = "";
export let createdByName: string | undefined;
export let avatar: string | undefined;
import logo from "../../../../../static/huggingchat/logo.svg?raw";
</script>
<div class="flex h-full w-full flex-col items-center justify-center bg... | chat-ui/src/routes/assistant/[assistantId]/thumbnail.png/ChatThumbnail.svelte/0 | {
"file_path": "chat-ui/src/routes/assistant/[assistantId]/thumbnail.png/ChatThumbnail.svelte",
"repo_id": "chat-ui",
"token_count": 545
} | 51 |
import { refreshSessionCookie } from "$lib/server/auth";
import { collections } from "$lib/server/database";
import { ObjectId } from "mongodb";
import { DEFAULT_SETTINGS } from "$lib/types/Settings";
import { z } from "zod";
import type { UserinfoResponse } from "openid-client";
import { error, type Cookies } from "@s... | chat-ui/src/routes/login/callback/updateUser.ts/0 | {
"file_path": "chat-ui/src/routes/login/callback/updateUser.ts",
"repo_id": "chat-ui",
"token_count": 1216
} | 52 |
import { base } from "$app/paths";
import { authCondition, requiresUser } from "$lib/server/auth";
import { collections } from "$lib/server/database";
import { fail, type Actions, redirect } from "@sveltejs/kit";
import { ObjectId } from "mongodb";
import { z } from "zod";
import { sha256 } from "$lib/utils/sha256";
i... | chat-ui/src/routes/settings/assistants/new/+page.server.ts/0 | {
"file_path": "chat-ui/src/routes/settings/assistants/new/+page.server.ts",
"repo_id": "chat-ui",
"token_count": 1200
} | 53 |
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
SPEED_TEST_N_EXAMPLES = 500_000
RESULTS_BASEPATH, RESULTS_FILENAME = os.path.split(__file__)
RESULTS_FILE_PATH = os.path.join(RESULTS_BASEPATH, "results", RESULTS_FILENAME.replace(".py", ".json"))
@get_d... | datasets/benchmarks/benchmark_indices_mapping.py/0 | {
"file_path": "datasets/benchmarks/benchmark_indices_mapping.py",
"repo_id": "datasets",
"token_count": 677
} | 54 |
# The cache
The cache is one of the reasons why 🤗 Datasets is so efficient. It stores previously downloaded and processed datasets so when you need to use them again, they are reloaded directly from the cache. This avoids having to download a dataset all over again, or reapplying processing functions. Even after you ... | datasets/docs/source/about_cache.mdx/0 | {
"file_path": "datasets/docs/source/about_cache.mdx",
"repo_id": "datasets",
"token_count": 909
} | 55 |
# Search index
[FAISS](https://github.com/facebookresearch/faiss) and [Elasticsearch](https://www.elastic.co/elasticsearch/) enables searching for examples in a dataset. This can be useful when you want to retrieve specific examples from a dataset that are relevant to your NLP task. For example, if you are working on ... | datasets/docs/source/faiss_es.mdx/0 | {
"file_path": "datasets/docs/source/faiss_es.mdx",
"repo_id": "datasets",
"token_count": 1830
} | 56 |
# Process text data
This guide shows specific methods for processing text datasets. Learn how to:
- Tokenize a dataset with [`~Dataset.map`].
- Align dataset labels with label ids for NLI datasets.
For a guide on how to process any type of dataset, take a look at the <a class="underline decoration-sky-400 decoration... | datasets/docs/source/nlp_process.mdx/0 | {
"file_path": "datasets/docs/source/nlp_process.mdx",
"repo_id": "datasets",
"token_count": 1109
} | 57 |
# Overview
Welcome to the 🤗 Datasets tutorials! These beginner-friendly tutorials will guide you through the fundamentals of working with 🤗 Datasets. You'll load and prepare a dataset for training with your machine learning framework of choice. Along the way, you'll learn how to load different dataset configurations... | datasets/docs/source/tutorial.md/0 | {
"file_path": "datasets/docs/source/tutorial.md",
"repo_id": "datasets",
"token_count": 311
} | 58 |
# 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/cer/cer.py/0 | {
"file_path": "datasets/metrics/cer/cer.py",
"repo_id": "datasets",
"token_count": 2133
} | 59 |
# Metric Card for Exact Match
## Metric Description
A given predicted string's exact match score is 1 if it is the exact same as its reference string, and is 0 otherwise.
- **Example 1**: The exact match score of prediction "Happy Birthday!" is 0, given its reference is "Happy New Year!".
- **Example 2**: The exact ... | datasets/metrics/exact_match/README.md/0 | {
"file_path": "datasets/metrics/exact_match/README.md",
"repo_id": "datasets",
"token_count": 1508
} | 60 |
# Metric Card for Matthews Correlation Coefficient
## Metric Description
The Matthews correlation coefficient is used in machine learning as a
measure of the quality of binary and multiclass classifications. It takes
into account true and false positives and negatives and is generally
regarded as a balanced measure wh... | datasets/metrics/matthews_correlation/README.md/0 | {
"file_path": "datasets/metrics/matthews_correlation/README.md",
"repo_id": "datasets",
"token_count": 1251
} | 61 |
# Metric Card for Recall
## Metric Description
Recall is the fraction of the positive examples that were correctly labeled by the model as positive. It can be computed with the equation:
Recall = TP / (TP + FN)
Where TP is the number of true positives and FN is the number of false negatives.
## How to Use
At mini... | datasets/metrics/recall/README.md/0 | {
"file_path": "datasets/metrics/recall/README.md",
"repo_id": "datasets",
"token_count": 1704
} | 62 |
# 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/squad.py/0 | {
"file_path": "datasets/metrics/squad/squad.py",
"repo_id": "datasets",
"token_count": 1933
} | 63 |
# Copyright 2022 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/xtreme_s/xtreme_s.py/0 | {
"file_path": "datasets/metrics/xtreme_s/xtreme_s.py",
"repo_id": "datasets",
"token_count": 4467
} | 64 |
import os
from argparse import ArgumentParser
from pathlib import Path
from shutil import copyfile
from typing import List
from datasets import config
from datasets.builder import DatasetBuilder
from datasets.commands import BaseDatasetsCLICommand
from datasets.download.download_config import DownloadConfig
from datas... | datasets/src/datasets/commands/run_beam.py/0 | {
"file_path": "datasets/src/datasets/commands/run_beam.py",
"repo_id": "datasets",
"token_count": 3193
} | 65 |
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class Translation:
"""`FeatureConnector` for translations with fixed languages per example.
Here for ... | datasets/src/datasets/features/translation.py/0 | {
"file_path": "datasets/src/datasets/features/translation.py",
"repo_id": "datasets",
"token_count": 1680
} | 66 |
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class GeneratorDatasetInputStream(AbstractDatasetInputStream):
def __init__(
self,
generator: Callable,
features: Optional... | datasets/src/datasets/io/generator.py/0 | {
"file_path": "datasets/src/datasets/io/generator.py",
"repo_id": "datasets",
"token_count": 896
} | 67 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, ClassLabel, Features
from .base import TaskTemplate
@dataclass(frozen=True)
class AudioClassification(TaskTemplate):
task: str = field(default="audio-classification", metadata={"include_in_asdict_... | datasets/src/datasets/tasks/audio_classification.py/0 | {
"file_path": "datasets/src/datasets/tasks/audio_classification.py",
"repo_id": "datasets",
"token_count": 487
} | 68 |
"""Contains utilities to flag a feature as "experimental" in datasets."""
import warnings
from functools import wraps
from typing import Callable
def experimental(fn: Callable) -> Callable:
"""Decorator to flag a feature as experimental.
An experimental feature trigger a warning when used as it might be subj... | datasets/src/datasets/utils/experimental.py/0 | {
"file_path": "datasets/src/datasets/utils/experimental.py",
"repo_id": "datasets",
"token_count": 385
} | 69 |
[
"unknown",
"n<1K",
"1K<n<10K",
"10K<n<100K",
"100K<n<1M",
"1M<n<10M",
"10M<n<100M",
"100M<n<1B",
"1B<n<10B",
"10B<n<100B",
"100B<n<1T",
"n>1T"
]
| datasets/src/datasets/utils/resources/size_categories.json/0 | {
"file_path": "datasets/src/datasets/utils/resources/size_categories.json",
"repo_id": "datasets",
"token_count": 124
} | 70 |
import pytest
DATASET_LOADING_SCRIPT_NAME = "__dummy_dataset1__"
DATASET_LOADING_SCRIPT_CODE = """
import json
import os
import datasets
REPO_URL = "https://huggingface.co/datasets/hf-internal-testing/raw_jsonl/resolve/main/"
URLS = {"train": REPO_URL + "wikiann-bn-train.jsonl", "validation": REPO_URL + "wikiann-... | datasets/tests/commands/conftest.py/0 | {
"file_path": "datasets/tests/commands/conftest.py",
"repo_id": "datasets",
"token_count": 1193
} | 71 |
import os
import textwrap
import pyarrow as pa
import pytest
from datasets import ClassLabel, Features, Image
from datasets.packaged_modules.csv.csv import Csv
from ..utils import require_pil
@pytest.fixture
def csv_file(tmp_path):
filename = tmp_path / "file.csv"
data = textwrap.dedent(
"""\
... | datasets/tests/packaged_modules/test_csv.py/0 | {
"file_path": "datasets/tests/packaged_modules/test_csv.py",
"repo_id": "datasets",
"token_count": 1672
} | 72 |
import json
import os
from pathlib import Path
import pytest
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename
URL = "http://www.mocksite.com/file1.txt"
CONTENT = '"text": ["foo", "fo... | datasets/tests/test_download_manager.py/0 | {
"file_path": "datasets/tests/test_download_manager.py",
"repo_id": "datasets",
"token_count": 2407
} | 73 |
import os
import pickle
import tempfile
import time
from multiprocessing import Pool
from unittest import TestCase
import pytest
from datasets.features import Features, Sequence, Value
from datasets.metric import Metric, MetricInfo
from .utils import require_tf, require_torch
class DummyMetric(Metric):
def _in... | datasets/tests/test_metric.py/0 | {
"file_path": "datasets/tests/test_metric.py",
"repo_id": "datasets",
"token_count": 10533
} | 74 |
import pytest
from datasets import inspect_metric, list_metrics, load_metric
@pytest.fixture
def mock_emitted_deprecation_warnings(monkeypatch):
monkeypatch.setattr("datasets.utils.deprecation_utils._emitted_deprecation_warnings", set())
# Used by list_metrics
@pytest.fixture
def mock_hfh(monkeypatch):
cla... | datasets/tests/test_warnings.py/0 | {
"file_path": "datasets/tests/test_warnings.py",
"repo_id": "datasets",
"token_count": 473
} | 75 |
# Train your first Deep Reinforcement Learning Agent 🤖 [[hands-on]]
<CourseFloatingBanner classNames="absolute z-10 right-0 top-0"
notebooks={[
{label: "Google Colab", value: "https://colab.research.google.com/github/huggingface/deep-rl-class/blob/main/notebooks/unit1/unit1.ipynb"}
]}
... | deep-rl-class/units/en/unit1/hands-on.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit1/hands-on.mdx",
"repo_id": "deep-rl-class",
"token_count": 9469
} | 76 |
# Mid-way Recap [[mid-way-recap]]
Before diving into Q-Learning, let's summarize what we've just learned.
We have two types of value-based functions:
- State-value function: outputs the expected return if **the agent starts at a given state and acts according to the policy forever after.**
- Action-value function: o... | deep-rl-class/units/en/unit2/mid-way-recap.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit2/mid-way-recap.mdx",
"repo_id": "deep-rl-class",
"token_count": 317
} | 77 |
# Additional Readings
These are **optional readings** if you want to go deeper.
## Introduction to Policy Optimization
- [Part 3: Intro to Policy Optimization - Spinning Up documentation](https://spinningup.openai.com/en/latest/spinningup/rl_intro3.html)
## Policy Gradient
- [https://johnwlambert.github.io/polic... | deep-rl-class/units/en/unit4/additional-readings.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit4/additional-readings.mdx",
"repo_id": "deep-rl-class",
"token_count": 281
} | 78 |
# The Pyramid environment
The goal in this environment is to train our agent to **get the gold brick on the top of the Pyramid. To do that, it needs to press a button to spawn a Pyramid, navigate to the Pyramid, knock it over, and move to the gold brick at the top**.
<img src="https://huggingface.co/datasets/huggingf... | deep-rl-class/units/en/unit5/pyramids.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit5/pyramids.mdx",
"repo_id": "deep-rl-class",
"token_count": 645
} | 79 |
# Quiz
The best way to learn and [to avoid the illusion of competence](https://www.coursera.org/lecture/learning-how-to-learn/illusions-of-competence-BuFzf) **is to test yourself.** This will help you to find **where you need to reinforce your knowledge**.
### Q1: Chose the option which fits better when comparing di... | deep-rl-class/units/en/unit7/quiz.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit7/quiz.mdx",
"repo_id": "deep-rl-class",
"token_count": 1361
} | 80 |
# Let's train and play with Huggy 🐶 [[train]]
<CourseFloatingBanner classNames="absolute z-10 right-0 top-0"
notebooks={[
{label: "Google Colab", value: "https://colab.research.google.com/github/huggingface/deep-rl-class/blob/master/notebooks/bonus-unit1/bonus-unit1.ipynb"}
... | deep-rl-class/units/en/unitbonus1/train.mdx/0 | {
"file_path": "deep-rl-class/units/en/unitbonus1/train.mdx",
"repo_id": "deep-rl-class",
"token_count": 4009
} | 81 |
# Student Works
Since the launch of the Deep Reinforcement Learning Course, **many students have created amazing projects that you should check out and consider participating in**.
If you've created an interesting project, don't hesitate to [add it to this list by opening a pull request on the GitHub repository](http... | deep-rl-class/units/en/unitbonus3/student-works.mdx/0 | {
"file_path": "deep-rl-class/units/en/unitbonus3/student-works.mdx",
"repo_id": "deep-rl-class",
"token_count": 629
} | 82 |
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
} | 83 |
<!---
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... | diffusers/docs/README.md/0 | {
"file_path": "diffusers/docs/README.md",
"repo_id": "diffusers",
"token_count": 3146
} | 84 |
<!--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/en/optimization/memory.md/0 | {
"file_path": "diffusers/docs/source/en/optimization/memory.md",
"repo_id": "diffusers",
"token_count": 4135
} | 85 |
<!--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/en/training/dreambooth.md/0 | {
"file_path": "diffusers/docs/source/en/training/dreambooth.md",
"repo_id": "diffusers",
"token_count": 6165
} | 86 |
<!--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/en/tutorials/using_peft_for_inference.md/0 | {
"file_path": "diffusers/docs/source/en/tutorials/using_peft_for_inference.md",
"repo_id": "diffusers",
"token_count": 3052
} | 87 |
<!--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/en/using-diffusers/inpaint.md/0 | {
"file_path": "diffusers/docs/source/en/using-diffusers/inpaint.md",
"repo_id": "diffusers",
"token_count": 14132
} | 88 |
<!--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/en/using-diffusers/svd.md/0 | {
"file_path": "diffusers/docs/source/en/using-diffusers/svd.md",
"repo_id": "diffusers",
"token_count": 1762
} | 89 |
# 학습을 위한 데이터셋 만들기
[Hub](https://huggingface.co/datasets?task_categories=task_categories:text-to-image&sort=downloads) 에는 모델 교육을 위한 많은 데이터셋이 있지만,
관심이 있거나 사용하고 싶은 데이터셋을 찾을 수 없는 경우 🤗 [Datasets](hf.co/docs/datasets) 라이브러리를 사용하여 데이터셋을 만들 수 있습니다.
데이터셋 구조는 모델을 학습하려는 작업에 따라 달라집니다.
가장 기본적인 데이터셋 구조는 unconditional 이미지 생성과 같은 작업... | diffusers/docs/source/ko/training/create_dataset.md/0 | {
"file_path": "diffusers/docs/source/ko/training/create_dataset.md",
"repo_id": "diffusers",
"token_count": 3214
} | 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/custom_pipeline_examples.md/0 | {
"file_path": "diffusers/docs/source/ko/using-diffusers/custom_pipeline_examples.md",
"repo_id": "diffusers",
"token_count": 10865
} | 91 |
<!--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/weighted_prompts.md/0 | {
"file_path": "diffusers/docs/source/ko/using-diffusers/weighted_prompts.md",
"repo_id": "diffusers",
"token_count": 3376
} | 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/pipeline_animatediff_img2video.py/0 | {
"file_path": "diffusers/examples/community/pipeline_animatediff_img2video.py",
"repo_id": "diffusers",
"token_count": 20519
} | 93 |
# 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/sd_text2img_k_diffusion.py/0 | {
"file_path": "diffusers/examples/community/sd_text2img_k_diffusion.py",
"repo_id": "diffusers",
"token_count": 9725
} | 94 |
# Based on stable_diffusion_reference.py
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import numpy as np
import PIL.Image
import torch
from diffusers import StableDiffusionXLPipeline
from diffusers.models.attention import BasicTransformerBlock
from diffusers.models.unets.unet_2d_blocks import... | diffusers/examples/community/stable_diffusion_xl_reference.py/0 | {
"file_path": "diffusers/examples/community/stable_diffusion_xl_reference.py",
"repo_id": "diffusers",
"token_count": 18770
} | 95 |
# DreamBooth training example for Stable Diffusion XL (SDXL)
[DreamBooth](https://arxiv.org/abs/2208.12242) is a method to personalize text2image models like stable diffusion given just a few (3~5) images of a subject.
The `train_dreambooth_lora_sdxl.py` script shows how to implement the training procedure and adapt ... | diffusers/examples/dreambooth/README_sdxl.md/0 | {
"file_path": "diffusers/examples/dreambooth/README_sdxl.md",
"repo_id": "diffusers",
"token_count": 2789
} | 96 |
# coding=utf-8
# Copyright 2023 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/instruct_pix2pix/test_instruct_pix2pix.py/0 | {
"file_path": "diffusers/examples/instruct_pix2pix/test_instruct_pix2pix.py",
"repo_id": "diffusers",
"token_count": 1824
} | 97 |
# Consistency Training
`train_cm_ct_unconditional.py` trains a consistency model (CM) from scratch following the consistency training (CT) algorithm introduced in [Consistency Models](https://arxiv.org/abs/2303.01469) and refined in [Improved Techniques for Training Consistency Models](https://arxiv.org/abs/2310.14189... | diffusers/examples/research_projects/consistency_training/README.md/0 | {
"file_path": "diffusers/examples/research_projects/consistency_training/README.md",
"repo_id": "diffusers",
"token_count": 413
} | 98 |
# coding=utf-8
# Copyright 2023 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 r... | diffusers/examples/research_projects/lora/train_text_to_image_lora.py/0 | {
"file_path": "diffusers/examples/research_projects/lora/train_text_to_image_lora.py",
"repo_id": "diffusers",
"token_count": 18941
} | 99 |
#!/usr/bin/env python
# coding=utf-8
# Copyright 2023 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/research_projects/onnxruntime/text_to_image/train_text_to_image.py/0 | {
"file_path": "diffusers/examples/research_projects/onnxruntime/text_to_image/train_text_to_image.py",
"repo_id": "diffusers",
"token_count": 16892
} | 100 |
import time
import jax
import jax.numpy as jnp
import numpy as np
from flax.jax_utils import replicate
from jax import pmap
# Let's cache the model compilation, so that it doesn't take as long the next time around.
from jax.experimental.compilation_cache import compilation_cache as cc
from diffusers import FlaxStabl... | diffusers/examples/research_projects/sdxl_flax/sdxl_single_aot.py/0 | {
"file_path": "diffusers/examples/research_projects/sdxl_flax/sdxl_single_aot.py",
"repo_id": "diffusers",
"token_count": 1969
} | 101 |
# coding=utf-8
# Copyright 2023 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 r... | diffusers/examples/text_to_image/train_text_to_image_lora.py/0 | {
"file_path": "diffusers/examples/text_to_image/train_text_to_image_lora.py",
"repo_id": "diffusers",
"token_count": 17853
} | 102 |
# Würstchen text-to-image fine-tuning
## Running locally with PyTorch
Before running the scripts, make sure to install the library's training dependencies:
**Important**
To make sure you can successfully run the latest versions of the example scripts, we highly recommend **installing from source** and keeping the i... | diffusers/examples/wuerstchen/text_to_image/README.md/0 | {
"file_path": "diffusers/examples/wuerstchen/text_to_image/README.md",
"repo_id": "diffusers",
"token_count": 1206
} | 103 |
import argparse
import os
import torch
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNet2DModel,
)
TEST_UNET_CONFIG = {
"sample_size": 32,
"in_channels": 3,
"out_channels": 3,
"layers_per_block": 2,
"num_class_embeds": 1000,
"block_out_channel... | diffusers/scripts/convert_consistency_to_diffusers.py/0 | {
"file_path": "diffusers/scripts/convert_consistency_to_diffusers.py",
"repo_id": "diffusers",
"token_count": 5773
} | 104 |
import json
import os
import torch
from diffusers import UNet1DModel
os.makedirs("hub/hopper-medium-v2/unet/hor32", exist_ok=True)
os.makedirs("hub/hopper-medium-v2/unet/hor128", exist_ok=True)
os.makedirs("hub/hopper-medium-v2/value_function", exist_ok=True)
def unet(hor):
if hor == 128:
down_block_... | diffusers/scripts/convert_models_diffuser_to_diffusers.py/0 | {
"file_path": "diffusers/scripts/convert_models_diffuser_to_diffusers.py",
"repo_id": "diffusers",
"token_count": 1700
} | 105 |
import argparse
import safetensors.torch
from diffusers import AutoencoderTiny
"""
Example - From the diffusers root directory:
Download the weights:
```sh
$ wget -q https://huggingface.co/madebyollin/taesd/resolve/main/taesd_encoder.safetensors
$ wget -q https://huggingface.co/madebyollin/taesd/resolve/main/taesd... | diffusers/scripts/convert_tiny_autoencoder_to_diffusers.py/0 | {
"file_path": "diffusers/scripts/convert_tiny_autoencoder_to_diffusers.py",
"repo_id": "diffusers",
"token_count": 990
} | 106 |
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
# Copyright (c) 2022, NVIDIA CORPORATION. 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.a... | diffusers/src/diffusers/configuration_utils.py/0 | {
"file_path": "diffusers/src/diffusers/configuration_utils.py",
"repo_id": "diffusers",
"token_count": 13484
} | 107 |
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable... | diffusers/src/diffusers/loaders/single_file_utils.py/0 | {
"file_path": "diffusers/src/diffusers/loaders/single_file_utils.py",
"repo_id": "diffusers",
"token_count": 25510
} | 108 |
# 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/src/diffusers/models/autoencoders/consistency_decoder_vae.py/0 | {
"file_path": "diffusers/src/diffusers/models/autoencoders/consistency_decoder_vae.py",
"repo_id": "diffusers",
"token_count": 8129
} | 109 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
# `TemporalConvLayer` Copyright 2023 Alibaba DAMO-VILAB, The ModelScope Team and The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
#... | diffusers/src/diffusers/models/resnet.py/0 | {
"file_path": "diffusers/src/diffusers/models/resnet.py",
"repo_id": "diffusers",
"token_count": 15038
} | 110 |
from ...utils import is_flax_available, is_torch_available
if is_torch_available():
from .unet_1d import UNet1DModel
from .unet_2d import UNet2DModel
from .unet_2d_condition import UNet2DConditionModel
from .unet_3d_condition import UNet3DConditionModel
from .unet_i2vgen_xl import I2VGenXLUNet
... | diffusers/src/diffusers/models/unets/__init__.py/0 | {
"file_path": "diffusers/src/diffusers/models/unets/__init__.py",
"repo_id": "diffusers",
"token_count": 245
} | 111 |
# 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/src/diffusers/models/vae_flax.py/0 | {
"file_path": "diffusers/src/diffusers/models/vae_flax.py",
"repo_id": "diffusers",
"token_count": 14480
} | 112 |
# 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/src/diffusers/pipelines/audioldm2/modeling_audioldm2.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/audioldm2/modeling_audioldm2.py",
"repo_id": "diffusers",
"token_count": 33881
} | 113 |
# Copyright 2023 Harutatsu Akiyama, Jinbin Bai, and The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2... | diffusers/src/diffusers/pipelines/controlnet/pipeline_controlnet_inpaint_sd_xl.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/controlnet/pipeline_controlnet_inpaint_sd_xl.py",
"repo_id": "diffusers",
"token_count": 39928
} | 114 |
# 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/src/diffusers/pipelines/deprecated/latent_diffusion_uncond/pipeline_latent_diffusion_uncond.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/deprecated/latent_diffusion_uncond/pipeline_latent_diffusion_uncond.py",
"repo_id": "diffusers",
"token_count": 2149
} | 115 |
# Copyright 2023 Alibaba DAMO-VILAB and The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unles... | diffusers/src/diffusers/pipelines/i2vgen_xl/pipeline_i2vgen_xl.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/i2vgen_xl/pipeline_i2vgen_xl.py",
"repo_id": "diffusers",
"token_count": 18258
} | 116 |
from typing import List, Optional, Union
import PIL.Image
import torch
from transformers import CLIPImageProcessor, CLIPTextModelWithProjection, CLIPTokenizer, CLIPVisionModelWithProjection
from ...models import PriorTransformer
from ...schedulers import UnCLIPScheduler
from ...utils import (
logging,
replace... | diffusers/src/diffusers/pipelines/kandinsky2_2/pipeline_kandinsky2_2_prior_emb2emb.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/kandinsky2_2/pipeline_kandinsky2_2_prior_emb2emb.py",
"repo_id": "diffusers",
"token_count": 11231
} | 117 |
# 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/src/diffusers/pipelines/paint_by_example/pipeline_paint_by_example.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/paint_by_example/pipeline_paint_by_example.py",
"repo_id": "diffusers",
"token_count": 12896
} | 118 |
from typing import TYPE_CHECKING
from ...utils import (
DIFFUSERS_SLOW_IMPORT,
OptionalDependencyNotAvailable,
_LazyModule,
get_objects_from_module,
is_flax_available,
is_k_diffusion_available,
is_k_diffusion_version,
is_onnx_available,
is_torch_available,
is_transformers_availa... | diffusers/src/diffusers/pipelines/stable_diffusion/__init__.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/stable_diffusion/__init__.py",
"repo_id": "diffusers",
"token_count": 3769
} | 119 |
# Copyright 2023 The InstructPix2Pix Authors and The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
... | diffusers/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_instruct_pix2pix.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_instruct_pix2pix.py",
"repo_id": "diffusers",
"token_count": 18762
} | 120 |
# 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/src/diffusers/pipelines/stable_diffusion_k_diffusion/pipeline_stable_diffusion_k_diffusion.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/stable_diffusion_k_diffusion/pipeline_stable_diffusion_k_diffusion.py",
"repo_id": "diffusers",
"token_count": 14511
} | 121 |
# 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/src/diffusers/pipelines/stable_diffusion_xl/pipeline_stable_diffusion_xl_img2img.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/stable_diffusion_xl/pipeline_stable_diffusion_xl_img2img.py",
"repo_id": "diffusers",
"token_count": 33880
} | 122 |
# Copyright 2023 Kakao Brain and The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... | diffusers/src/diffusers/pipelines/unclip/pipeline_unclip.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/unclip/pipeline_unclip.py",
"repo_id": "diffusers",
"token_count": 9941
} | 123 |
# Schedulers
For more information on the schedulers, please refer to the [docs](https://huggingface.co/docs/diffusers/api/schedulers/overview). | diffusers/src/diffusers/schedulers/README.md/0 | {
"file_path": "diffusers/src/diffusers/schedulers/README.md",
"repo_id": "diffusers",
"token_count": 46
} | 124 |
# Copyright 2023 FLAIR Lab and The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | diffusers/src/diffusers/schedulers/scheduling_deis_multistep.py/0 | {
"file_path": "diffusers/src/diffusers/schedulers/scheduling_deis_multistep.py",
"repo_id": "diffusers",
"token_count": 15822
} | 125 |
# Copyright 2023 Katherine Crowson and The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless... | diffusers/src/diffusers/schedulers/scheduling_lms_discrete_flax.py/0 | {
"file_path": "diffusers/src/diffusers/schedulers/scheduling_lms_discrete_flax.py",
"repo_id": "diffusers",
"token_count": 4682
} | 126 |
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