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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
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35
use crate::models::with_tracing::QMatMul; use crate::quantized_nn::{layer_norm, linear, Embedding, Linear}; pub use crate::quantized_var_builder::VarBuilder; use candle::{Module, Result, Tensor, D}; use candle_nn::LayerNorm; pub type Config = super::blip_text::Config; #[derive(Debug, Clone)] struct TextEmbeddings { ...
candle/candle-transformers/src/models/quantized_blip_text.rs/0
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use crate::models::with_tracing::{conv2d, linear, Conv2d, Linear}; use candle::{Module, ModuleT, Result, Tensor, D}; use candle_nn::{conv2d_no_bias, layer_norm, Activation, Conv2dConfig, VarBuilder}; use serde::Deserialize; use std::collections::HashMap; // https://github.com/huggingface/transformers/blob/main/src/tra...
candle/candle-transformers/src/models/segformer.rs/0
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37
#![allow(dead_code)] //! # Diffusion pipelines and models //! //! Noise schedulers can be used to set the trade-off between //! inference speed and quality. use candle::{Result, Tensor}; pub trait SchedulerConfig: std::fmt::Debug { fn build(&self, inference_steps: usize) -> Result<Box<dyn Scheduler>>; } /// This ...
candle/candle-transformers/src/models/stable_diffusion/schedulers.rs/0
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use candle::{Module, Result, Tensor}; use candle_nn::{linear, Linear, VarBuilder}; // A simplified version of: // https://github.com/huggingface/diffusers/blob/119ad2c3dc8a8fb8446a83f4bf6f20929487b47f/src/diffusers/models/attention_processor.py#L38 #[derive(Debug)] pub struct Attention { to_q: Linear, to_k: Li...
candle/candle-transformers/src/models/wuerstchen/attention_processor.rs/0
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## Running [llama2.c](https://github.com/karpathy/llama2.c) Examples Here, we provide two examples of how to run [llama2.c](https://github.com/karpathy/llama2.c) written in Rust using a Candle-compiled WASM binary and runtimes. ### Pure Rust UI To build and test the UI made in Rust you will need [Trunk](https://trun...
candle/candle-wasm-examples/llama2-c/README.md/0
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import init, { Model } from "./build/m.js"; async function fetchArrayBuffer(url) { const cacheName = "phi-mixformer-candle-cache"; const cache = await caches.open(cacheName); const cachedResponse = await cache.match(url); if (cachedResponse) { const data = await cachedResponse.arrayBuffer(); return new...
candle/candle-wasm-examples/phi/phiWorker.js/0
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use candle::{Device, Tensor}; use candle_transformers::generation::LogitsProcessor; pub use candle_transformers::models::quantized_t5::{ Config, T5EncoderModel, T5ForConditionalGeneration, VarBuilder, }; use candle_wasm_example_t5::console_log; use tokenizers::Tokenizer; use wasm_bindgen::prelude::*; const DEVICE:...
candle/candle-wasm-examples/t5/src/bin/m-quantized.rs/0
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pub const WITH_TIMER: bool = true; struct Timer { label: &'static str, } // impl Timer { // fn new(label: &'static str) -> Self { // if WITH_TIMER { // web_sys::console::time_with_label(label); // } // Self { label } // } // } impl Drop for Timer { fn drop(&mut sel...
candle/candle-wasm-examples/whisper/src/lib.rs/0
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//load the candle yolo wasm module import init, { Model, ModelPose } from "./build/m.js"; async function fetchArrayBuffer(url) { const cacheName = "yolo-candle-cache"; const cache = await caches.open(cacheName); const cachedResponse = await cache.match(url); if (cachedResponse) { const data = await cachedR...
candle/candle-wasm-examples/yolo/yoloWorker.js/0
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# syntax=docker/dockerfile:1 # read the doc: https://huggingface.co/docs/hub/spaces-sdks-docker # you will also find guides on how best to write your Dockerfile FROM node:20 as builder-production WORKDIR /app COPY --link --chown=1000 package-lock.json package.json ./ RUN --mount=type=cache,target=/app/.npm \ ...
chat-ui/Dockerfile/0
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import { ADMIN_API_SECRET, COOKIE_NAME, EXPOSE_API, MESSAGES_BEFORE_LOGIN, PARQUET_EXPORT_SECRET, } from "$env/static/private"; import type { Handle } from "@sveltejs/kit"; import { PUBLIC_GOOGLE_ANALYTICS_ID, PUBLIC_ORIGIN, PUBLIC_APP_DISCLAIMER, } from "$env/static/public"; import { collections } from "$lib/s...
chat-ui/src/hooks.server.ts/0
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<script lang="ts"> import { base } from "$app/paths"; import Logo from "$lib/components/icons/Logo.svelte"; import { switchTheme } from "$lib/switchTheme"; import { isAborted } from "$lib/stores/isAborted"; import { PUBLIC_APP_NAME, PUBLIC_ORIGIN } from "$env/static/public"; import NavConversationItem from "./Na...
chat-ui/src/lib/components/NavMenu.svelte/0
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<script lang="ts"> import { PUBLIC_APP_NAME, PUBLIC_VERSION } from "$env/static/public"; import { PUBLIC_ANNOUNCEMENT_BANNERS } from "$env/static/public"; import { PUBLIC_APP_DESCRIPTION } from "$env/static/public"; import Logo from "$lib/components/icons/Logo.svelte"; import { createEventDispatcher } from "svelte...
chat-ui/src/lib/components/chat/ChatIntroduction.svelte/0
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import type { Migration } from "."; import { getCollections } from "$lib/server/database"; import { ObjectId, type AnyBulkWriteOperation } from "mongodb"; import type { Assistant } from "$lib/types/Assistant"; import { generateSearchTokens } from "$lib/utils/searchTokens"; const migration: Migration = { _id: new Obje...
chat-ui/src/lib/migrations/routines/01-update-search-assistants.ts/0
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import type { TextGenerationStreamOutput } from "@huggingface/inference"; import type OpenAI from "openai"; import type { Stream } from "openai/streaming"; /** * Transform a stream of OpenAI.Chat.ChatCompletion into a stream of TextGenerationStreamOutput */ export async function* openAIChatToTextGenerationStream( c...
chat-ui/src/lib/server/endpoints/openai/openAIChatToTextGenerationStream.ts/0
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import { SEARXNG_QUERY_URL } from "$env/static/private"; export async function searchSearxng(query: string) { const abortController = new AbortController(); setTimeout(() => abortController.abort(), 10000); // Insert the query into the URL template let url = SEARXNG_QUERY_URL.replace("<query>", query); // Check...
chat-ui/src/lib/server/websearch/searchSearxng.ts/0
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import type { Timestamps } from "./Timestamps"; export interface ConversationStats extends Timestamps { date: { at: Date; span: "day" | "week" | "month"; field: "updatedAt" | "createdAt"; }; type: "conversation" | "message"; /** _id => number of conversations/messages in the month */ distinct: "sessionId" ...
chat-ui/src/lib/types/ConversationStats.ts/0
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export interface GAEvent { hitType: "event"; eventCategory: string; eventAction: string; eventLabel?: string; eventValue?: number; } // Send a Google Analytics event export function sendAnalyticsEvent({ eventCategory, eventAction, eventLabel, eventValue, }: Omit<GAEvent, "hitType">): void { // Mandatory fiel...
chat-ui/src/lib/utils/analytics.ts/0
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type UUID = ReturnType<typeof crypto.randomUUID>; export function randomUUID(): UUID { // Only on old safari / ios if (!("randomUUID" in crypto)) { return "10000000-1000-4000-8000-100000000000".replace(/[018]/g, (c) => ( Number(c) ^ (crypto.getRandomValues(new Uint8Array(1))[0] & (15 >> (Number(c) / 4))...
chat-ui/src/lib/utils/randomUuid.ts/0
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import { describe, expect, it } from "vitest"; import { isMessageId } from "./isMessageId"; import { v4 } from "uuid"; describe("isMessageId", () => { it("should return true for a valid message id", () => { expect(isMessageId(v4())).toBe(true); }); it("should return false for an invalid message id", () => { exp...
chat-ui/src/lib/utils/tree/isMessageId.spec.ts/0
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<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
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import { refreshSessionCookie } from "$lib/server/auth"; import { collections } from "$lib/server/database"; import { ObjectId } from "mongodb"; import { DEFAULT_SETTINGS } from "$lib/types/Settings"; import { z } from "zod"; import type { UserinfoResponse } from "openid-client"; import { error, type Cookies } from "@s...
chat-ui/src/routes/login/callback/updateUser.ts/0
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import { base } from "$app/paths"; import { redirect } from "@sveltejs/kit"; export async function load({ parent, params }) { const data = await parent(); const assistant = data.settings.assistants.find((id) => id === params.assistantId); if (!assistant) { throw redirect(302, `${base}/assistant/${params.assista...
chat-ui/src/routes/settings/(nav)/assistants/[assistantId]/+page.ts/0
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# How to contribute to Datasets? [![Contributor Covenant](https://img.shields.io/badge/Contributor%20Covenant-2.0-4baaaa.svg)](CODE_OF_CONDUCT.md) Datasets is an open source project, so all contributions and suggestions are welcome. You can contribute in many different ways: giving ideas, answering questions, reporti...
datasets/CONTRIBUTING.md/0
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# Load audio data You can load an audio dataset using the [`Audio`] feature that automatically decodes and resamples the audio files when you access the examples. Audio decoding is based on the [`soundfile`](https://github.com/bastibe/python-soundfile) python package, which uses the [`libsndfile`](https://github.com/l...
datasets/docs/source/audio_load.mdx/0
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# Process 🤗 Datasets provides many tools for modifying the structure and content of a dataset. These tools are important for tidying up a dataset, creating additional columns, converting between features and formats, and much more. This guide will show you how to: - Reorder rows and split the dataset. - Rename and ...
datasets/docs/source/process.mdx/0
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# Metric Card for Accuracy ## Metric Description Accuracy is the proportion of correct predictions among the total number of cases processed. It can be computed with: Accuracy = (TP + TN) / (TP + TN + FP + FN) Where: TP: True positive TN: True negative FP: False positive FN: False negative ## How to Use At minim...
datasets/metrics/accuracy/README.md/0
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# 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/comet/comet.py/0
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# Metric Card for Google BLEU (GLEU) ## Metric Description The BLEU score has some undesirable properties when used for single sentences, as it was designed to be a corpus measure. The Google BLEU score, also known as GLEU score, is designed to limit these undesirable properties when used for single sentences. To ca...
datasets/metrics/google_bleu/README.md/0
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# Metric Card for MSE ## Metric Description Mean Squared Error(MSE) represents the average of the squares of errors -- i.e. the average squared difference between the estimated values and the actual values. ![image](https://user-images.githubusercontent.com/14205986/165999302-eba3702d-81e3-4363-9c0e-d3bfceb7ec5a.pn...
datasets/metrics/mse/README.md/0
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# Metric Card for SARI ## Metric description SARI (***s**ystem output **a**gainst **r**eferences and against the **i**nput sentence*) is a metric used for evaluating automatic text simplification systems. The metric compares the predicted simplified sentences against the reference and the source sentences. It expli...
datasets/metrics/sari/README.md/0
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# 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/ter/ter.py/0
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# Copyright 2020 The HuggingFace Datasets Authors and the TensorFlow Datasets Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # Unless required by applicable law or agreed to in wr...
datasets/src/datasets/arrow_writer.py/0
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# Copyright 2020 The TensorFlow Datasets Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or a...
datasets/src/datasets/download/download_manager.py/0
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# Copyright 2020 The HuggingFace Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to...
datasets/src/datasets/formatting/np_formatter.py/0
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# Copyright 2020 The HuggingFace Datasets Authors and the TensorFlow Datasets Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # U...
datasets/src/datasets/keyhash.py/0
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from dataclasses import dataclass from typing import Callable, Optional import datasets @dataclass class GeneratorConfig(datasets.BuilderConfig): generator: Optional[Callable] = None gen_kwargs: Optional[dict] = None features: Optional[datasets.Features] = None def __post_init__(self): asser...
datasets/src/datasets/packaged_modules/generator/generator.py/0
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# # Copyright (c) 2017-2021 NVIDIA CORPORATION. All rights reserved. # This file coems from the WebDataset library. # See the LICENSE file for licensing terms (BSD-style). # """ Binary tensor encodings for PyTorch and NumPy. This defines efficient binary encodings for tensors. The format is 8 byte aligned and can be ...
datasets/src/datasets/packaged_modules/webdataset/_tenbin.py/0
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import copy from dataclasses import dataclass, field from typing import ClassVar, Dict from ..features import ClassLabel, Features, Value from .base import TaskTemplate @dataclass(frozen=True) class TextClassification(TaskTemplate): # `task` is not a ClassVar since we want it to be part of the `asdict` output fo...
datasets/src/datasets/tasks/text_classification.py/0
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import re import textwrap from collections import Counter from itertools import groupby from operator import itemgetter from pathlib import Path from typing import Any, ClassVar, Dict, List, Optional, Tuple, Union import yaml from huggingface_hub import DatasetCardData from ..config import METADATA_CONFIGS_FIELD from...
datasets/src/datasets/utils/metadata.py/0
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# Copyright 2020 The HuggingFace Datasets Authors and the TensorFlow Datasets Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # U...
datasets/src/datasets/utils/version.py/0
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import contextlib import copy import itertools import json import os import pickle import re import sys import tempfile from functools import partial from pathlib import Path from unittest import TestCase from unittest.mock import MagicMock, patch import numpy as np import numpy.testing as npt import pandas as pd impo...
datasets/tests/test_arrow_dataset.py/0
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import datetime from pathlib import Path from unittest import TestCase import numpy as np import pandas as pd import pyarrow as pa import pytest from datasets import Audio, Features, Image, IterableDataset from datasets.formatting import NumpyFormatter, PandasFormatter, PythonFormatter, query_table from datasets.form...
datasets/tests/test_formatting.py/0
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import os import tempfile from functools import partial from unittest import TestCase from unittest.mock import patch import numpy as np import pytest from datasets.arrow_dataset import Dataset from datasets.search import ElasticSearchIndex, FaissIndex, MissingIndex from .utils import require_elasticsearch, require_...
datasets/tests/test_search.py/0
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# Discord 101 [[discord-101]] Hey there! My name is Huggy, the dog 🐕, and I'm looking forward to train with you during this RL Course! Although I don't know much about fetching sticks (yet), I know one or two things about Discord. So I wrote this guide to help you learn about it! <img src="https://huggingface.co/dat...
deep-rl-class/units/en/unit0/discord101.mdx/0
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# Additional Readings [[additional-readings]] These are **optional readings** if you want to go deeper. ## Monte Carlo and TD Learning [[mc-td]] To dive deeper into Monte Carlo and Temporal Difference Learning: - <a href="https://stats.stackexchange.com/questions/355820/why-do-temporal-difference-td-methods-have-lo...
deep-rl-class/units/en/unit2/additional-readings.mdx/0
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# Conclusion [[conclusion]] Congrats on finishing this chapter! There was a lot of information. And congrats on finishing the tutorial. You’ve just trained your first Deep Q-Learning agent and shared it on the Hub 🥳. Take time to really grasp the material before continuing. Don't hesitate to train your agent in oth...
deep-rl-class/units/en/unit3/conclusion.mdx/0
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# 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: What are the advantages of policy-gradient over valu...
deep-rl-class/units/en/unit4/quiz.mdx/0
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# 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: Which of the following interpretations of bias-varia...
deep-rl-class/units/en/unit6/quiz.mdx/0
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# Introduction to PPO with Sample-Factory <img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit9/thumbnail2.png" alt="thumbnail"/> In this second part of Unit 8, we'll get deeper into PPO optimization by using [Sample-Factory](https://samplefactory.dev/), an **asynchr...
deep-rl-class/units/en/unit8/introduction-sf.mdx/0
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# Godot RL Agents [Godot RL Agents](https://github.com/edbeeching/godot_rl_agents) is an Open Source package that allows video game creators, AI researchers, and hobbyists the opportunity **to learn complex behaviors for their Non Player Characters or agents**. The library provides: - An interface between games crea...
deep-rl-class/units/en/unitbonus3/godotrl.mdx/0
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import glob import sys import pandas as pd from huggingface_hub import hf_hub_download, upload_file from huggingface_hub.utils._errors import EntryNotFoundError sys.path.append(".") from utils import BASE_PATH, FINAL_CSV_FILE, GITHUB_SHA, REPO_ID, collate_csv # noqa: E402 def has_previous_benchmark() -> str: ...
diffusers/benchmarks/push_results.py/0
{ "file_path": "diffusers/benchmarks/push_results.py", "repo_id": "diffusers", "token_count": 1089 }
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<!--Copyright 2024 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
diffusers/docs/source/en/api/attnprocessor.md/0
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<!--Copyright 2024 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
diffusers/docs/source/en/api/models/overview.md/0
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<!--Copyright 2024 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to...
diffusers/docs/source/en/api/pipelines/kandinsky_v22.md/0
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<!--Copyright 2024 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
diffusers/docs/source/en/api/pipelines/stable_diffusion/depth2img.md/0
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<!--Copyright 2024 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
diffusers/docs/source/en/optimization/habana.md/0
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<!--Copyright 2024 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
diffusers/docs/source/en/training/distributed_inference.md/0
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<!--Copyright 2024 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
diffusers/docs/source/en/tutorials/tutorial_overview.md/0
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<!--Copyright 2024 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
diffusers/docs/source/en/using-diffusers/inference_with_lcm_lora.md/0
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<!--Copyright 2024 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
diffusers/docs/source/en/using-diffusers/sdxl.md/0
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<!--Copyright 2024 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
diffusers/docs/source/ja/tutorials/autopipeline.md/0
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<!--Copyright 2024 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
diffusers/docs/source/ko/optimization/xformers.md/0
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<!--Copyright 2024 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
diffusers/docs/source/ko/tutorials/tutorial_overview.md/0
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<!--Copyright 2024 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
diffusers/docs/source/ko/using-diffusers/schedulers.md/0
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<!--- Copyright 2024 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or a...
diffusers/examples/README.md/0
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from typing import Optional import torch from PIL import Image from tqdm.auto import tqdm from transformers import CLIPTextModel, CLIPTokenizer from diffusers import AutoencoderKL, DDIMScheduler, DiffusionPipeline, UNet2DConditionModel from diffusers.image_processor import VaeImageProcessor from diffusers.utils impor...
diffusers/examples/community/edict_pipeline.py/0
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# Copyright 2024 Bingxin Ke, ETH Zurich 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 # # U...
diffusers/examples/community/marigold_depth_estimation.py/0
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# Copyright 2024 The InstantX 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 l...
diffusers/examples/community/pipeline_stable_diffusion_xl_instantid.py/0
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# Inspired by: https://github.com/Mikubill/sd-webui-controlnet/discussions/1236 and https://github.com/Mikubill/sd-webui-controlnet/discussions/1280 from typing import Any, Callable, Dict, List, Optional, Tuple, Union import numpy as np import PIL.Image import torch from diffusers import StableDiffusionControlNetPipe...
diffusers/examples/community/stable_diffusion_controlnet_reference.py/0
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# Latent Consistency Distillation Example: [Latent Consistency Models (LCMs)](https://arxiv.org/abs/2310.04378) is a method to distill a latent diffusion model to enable swift inference with minimal steps. This example demonstrates how to use latent consistency distillation to distill stable-diffusion-v1.5 for inferen...
diffusers/examples/consistency_distillation/README.md/0
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#!/usr/bin/env python # coding=utf-8 # Copyright 2024 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LI...
diffusers/examples/controlnet/train_controlnet_flax.py/0
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import argparse import logging import math import os from pathlib import Path import jax import jax.numpy as jnp import numpy as np import optax import torch import torch.utils.checkpoint import transformers from flax import jax_utils from flax.training import train_state from flax.training.common_utils import shard f...
diffusers/examples/dreambooth/train_dreambooth_flax.py/0
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# coding=utf-8 # Copyright 2024 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
diffusers/examples/kandinsky2_2/text_to_image/train_text_to_image_lora_prior.py/0
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# !pip install opencv-python transformers accelerate import argparse import cv2 import numpy as np import torch from controlnetxs import ControlNetXSModel from PIL import Image from pipeline_controlnet_xs import StableDiffusionControlNetXSPipeline from diffusers.utils import load_image parser = argparse.ArgumentPar...
diffusers/examples/research_projects/controlnetxs/infer_sd_controlnetxs.py/0
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## Textual Inversion fine-tuning example [Textual inversion](https://arxiv.org/abs/2208.01618) is a method to personalize text2image models like stable diffusion on your own images using just 3-5 examples. The `textual_inversion.py` script shows how to implement the training procedure and adapt it for stable diffusion...
diffusers/examples/research_projects/intel_opts/textual_inversion/README.md/0
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## [Deprecated] Multi Token Textual Inversion **IMPORTART: This research project is deprecated. Multi Token Textual Inversion is now supported natively in [the official textual inversion example](https://github.com/huggingface/diffusers/tree/main/examples/textual_inversion#running-locally-with-pytorch).** The author ...
diffusers/examples/research_projects/multi_token_textual_inversion/README.md/0
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# PromptDiffusion Pipeline From the project [page](https://zhendong-wang.github.io/prompt-diffusion.github.io/) "With a prompt consisting of a task-specific example pair of images and text guidance, and a new query image, Prompt Diffusion can comprehend the desired task and generate the corresponding output image on ...
diffusers/examples/research_projects/promptdiffusion/README.md/0
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## Textual Inversion fine-tuning example [Textual inversion](https://arxiv.org/abs/2208.01618) is a method to personalize text2image models like stable diffusion on your own images using just 3-5 examples. The `textual_inversion.py` script shows how to implement the training procedure and adapt it for stable diffusion...
diffusers/examples/textual_inversion/README.md/0
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# Script for converting a Hugging Face Diffusers trained SDXL LoRAs to Kohya format # This means that you can input your diffusers-trained LoRAs and # Get the output to work with WebUIs such as AUTOMATIC1111, ComfyUI, SD.Next and others. # To get started you can find some cool `diffusers` trained LoRAs such as this cu...
diffusers/scripts/convert_diffusers_sdxl_lora_to_webui.py/0
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# coding=utf-8 # Copyright 2024 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/scripts/convert_ncsnpp_original_checkpoint_to_diffusers.py/0
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import argparse from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline if __name__ == "__main__": parser = argparse.ArgumentParser() parser.add_argument("--dump_path", default=None, type=str, required=True, help="Path to...
diffusers/scripts/convert_unclip_txt2img_to_image_variation.py/0
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# coding=utf-8 # Copyright 2024 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
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# coding=utf-8 # Copyright 2024 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
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# Copyright 2024 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
diffusers/src/diffusers/models/autoencoders/consistency_decoder_vae.py/0
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# Copyright 2024 The HuggingFace Team. All rights reserved. # `TemporalConvLayer` Copyright 2024 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": 14494 }
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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
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# Copyright 2024 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
diffusers/src/diffusers/models/upsampling.py/0
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from typing import TYPE_CHECKING from ...utils import ( DIFFUSERS_SLOW_IMPORT, OptionalDependencyNotAvailable, _LazyModule, get_objects_from_module, is_torch_available, is_transformers_available, is_transformers_version, ) _dummy_objects = {} _import_structure = {} try: if not (is_tr...
diffusers/src/diffusers/pipelines/audioldm2/__init__.py/0
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# Copyright 2024 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
diffusers/src/diffusers/pipelines/controlnet/pipeline_controlnet_inpaint.py/0
{ "file_path": "diffusers/src/diffusers/pipelines/controlnet/pipeline_controlnet_inpaint.py", "repo_id": "diffusers", "token_count": 36079 }
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from typing import TYPE_CHECKING from ....utils import DIFFUSERS_SLOW_IMPORT, _LazyModule _import_structure = {"pipeline_latent_diffusion_uncond": ["LDMPipeline"]} if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT: from .pipeline_latent_diffusion_uncond import LDMPipeline else: import sys sys.modules[__name__]...
diffusers/src/diffusers/pipelines/deprecated/latent_diffusion_uncond/__init__.py/0
{ "file_path": "diffusers/src/diffusers/pipelines/deprecated/latent_diffusion_uncond/__init__.py", "repo_id": "diffusers", "token_count": 190 }
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# Copyright 2024 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
diffusers/src/diffusers/pipelines/deprecated/stable_diffusion_variants/pipeline_stable_diffusion_inpaint_legacy.py/0
{ "file_path": "diffusers/src/diffusers/pipelines/deprecated/stable_diffusion_variants/pipeline_stable_diffusion_inpaint_legacy.py", "repo_id": "diffusers", "token_count": 18115 }
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# Copyright 2024 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
diffusers/src/diffusers/pipelines/free_init_utils.py/0
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# Copyright 2024 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
diffusers/src/diffusers/pipelines/kandinsky2_2/pipeline_kandinsky2_2_inpainting.py/0
{ "file_path": "diffusers/src/diffusers/pipelines/kandinsky2_2/pipeline_kandinsky2_2_inpainting.py", "repo_id": "diffusers", "token_count": 11058 }
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from dataclasses import dataclass from typing import List, Optional, Union import numpy as np import PIL.Image from ...utils import BaseOutput @dataclass class LEditsPPDiffusionPipelineOutput(BaseOutput): """ Output class for LEdits++ Diffusion pipelines. Args: images (`List[PIL.Image.Image]` o...
diffusers/src/diffusers/pipelines/ledits_pp/pipeline_output.py/0
{ "file_path": "diffusers/src/diffusers/pipelines/ledits_pp/pipeline_output.py", "repo_id": "diffusers", "token_count": 613 }
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import inspect from itertools import repeat from typing import Callable, List, Optional, Union import torch from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer from ...image_processor import VaeImageProcessor from ...models import AutoencoderKL, UNet2DConditionModel from ...pipelines.stable_diff...
diffusers/src/diffusers/pipelines/semantic_stable_diffusion/pipeline_semantic_stable_diffusion.py/0
{ "file_path": "diffusers/src/diffusers/pipelines/semantic_stable_diffusion/pipeline_semantic_stable_diffusion.py", "repo_id": "diffusers", "token_count": 18046 }
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# Copyright 2024 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
diffusers/src/diffusers/pipelines/stable_diffusion/pipeline_flax_stable_diffusion_inpaint.py/0
{ "file_path": "diffusers/src/diffusers/pipelines/stable_diffusion/pipeline_flax_stable_diffusion_inpaint.py", "repo_id": "diffusers", "token_count": 11428 }
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# Copyright 2024 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
diffusers/src/diffusers/pipelines/stable_diffusion/safety_checker.py/0
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# Copyright 2024 MultiDiffusion 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 # # Un...
diffusers/src/diffusers/pipelines/stable_diffusion_panorama/pipeline_stable_diffusion_panorama.py/0
{ "file_path": "diffusers/src/diffusers/pipelines/stable_diffusion_panorama/pipeline_stable_diffusion_panorama.py", "repo_id": "diffusers", "token_count": 22052 }
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