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use pyo3::exceptions::PyValueError; use pyo3::prelude::*; pub fn wrap_err(err: ::candle::Error) -> PyErr { PyErr::new::<PyValueError, _>(format!("{err:?}")) }
candle/candle-pyo3/src/utils.rs/0
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37
use candle::{DType, Device, IndexOp, Result, Tensor, D}; use candle_nn::{embedding, linear_b as linear, Embedding, LayerNorm, Linear, Module, VarBuilder}; fn layer_norm(size: usize, eps: f64, vb: VarBuilder) -> Result<LayerNorm> { let weight = vb.get(size, "weight")?; let bias = vb.get(size, "bias")?; Ok(L...
candle/candle-transformers/src/models/bigcode.rs/0
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38
use byteorder::{LittleEndian, ReadBytesExt}; use candle::{DType, Device, IndexOp, Result, Shape, Tensor}; use candle_nn::VarBuilder; use super::llama2_c::Config; pub struct TransformerWeights { // token embedding table token_embedding_table: Tensor, // (vocab_size, dim) // weights for rmsnorms rms_att...
candle/candle-transformers/src/models/llama2_c_weights.rs/0
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39
use crate::quantized_nn::{linear_b, Embedding, Linear, RmsNorm}; pub use crate::quantized_var_builder::VarBuilder; use crate::models::metavoice::repeat_interleave; use candle::{Module, Result, Tensor, D}; pub mod transformer { use super::*; type Config = crate::models::metavoice::transformer::Config; #[...
candle/candle-transformers/src/models/quantized_metavoice.rs/0
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40
pub use crate::models::with_tracing::Linear; use candle::{Result, Tensor}; use candle_nn::{Module, VarBuilder}; pub mod image_encoder; pub mod mask_decoder; pub mod prompt_encoder; pub mod sam; pub mod tiny_vit; pub mod transformer; pub fn linear(vb: VarBuilder, in_dim: usize, out_dim: usize, bias: bool) -> Result<Li...
candle/candle-transformers/src/models/segment_anything/mod.rs/0
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41
use candle::{Device, Result, Tensor}; pub fn linspace(start: f64, stop: f64, steps: usize) -> Result<Tensor> { if steps == 0 { Tensor::from_vec(Vec::<f64>::new(), steps, &Device::Cpu) } else if steps == 1 { Tensor::from_vec(vec![start], steps, &Device::Cpu) } else { let delta = (sto...
candle/candle-transformers/src/models/stable_diffusion/utils.rs/0
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42
use super::common::{AttnBlock, GlobalResponseNorm, LayerNormNoWeights, TimestepBlock, WLayerNorm}; use candle::{DType, Module, Result, Tensor, D}; use candle_nn::VarBuilder; #[derive(Debug)] pub struct ResBlockStageB { depthwise: candle_nn::Conv2d, norm: WLayerNorm, channelwise_lin1: candle_nn::Linear, ...
candle/candle-transformers/src/models/wuerstchen/diffnext.rs/0
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43
<html> <head> <meta content="text/html;charset=utf-8" http-equiv="Content-Type" /> <title>Candle Bert</title> </head> <body></body> </html> <!DOCTYPE html> <html> <head> <meta charset="UTF-8" /> <meta name="viewport" content="width=device-width, initial-scale=1.0" /> <style> @import u...
candle/candle-wasm-examples/bert/lib-example.html/0
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44
<html> <head> <meta content="text/html;charset=utf-8" http-equiv="Content-Type" /> <title>Candle Llama.c Rust/WASM</title> </head> <body></body> </html> <!DOCTYPE html> <html> <head> <meta charset="UTF-8" /> <meta name="viewport" content="width=device-width, initial-scale=1.0" /> <style> ...
candle/candle-wasm-examples/llama2-c/lib-example.html/0
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45
[package] name = "candle-wasm-example-sam" 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-trans...
candle/candle-wasm-examples/segment-anything/Cargo.toml/0
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46
export async function extractEmbeddings( worker, weightsURL, tokenizerURL, configURL, modelID, sentences, updateStatus, normalize_embeddings = true ) { return new Promise((resolve, reject) => { worker.postMessage({ weightsURL, tokenizerURL, configURL, modelID, sentenc...
candle/candle-wasm-examples/t5/utils.js/0
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47
[package] name = "candle-wasm-example-yolo" 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 } num-traits ...
candle/candle-wasm-examples/yolo/Cargo.toml/0
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48
pub fn add(left: usize, right: usize) -> usize { left + right } #[cfg(test)] mod tests { use super::*; #[test] fn it_works() { let result = add(2, 2); assert_eq!(result, 4); } }
candle/candle-wasm-tests/src/lib.rs/0
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49
import { navigating } from "$app/stores"; import { tick } from "svelte"; import { get } from "svelte/store"; const detachedOffset = 10; /** * @param node element to snap scroll to bottom * @param dependency pass in a dependency to update scroll on changes. */ export const snapScrollToBottom = (node: HTMLElement, d...
chat-ui/src/lib/actions/snapScrollToBottom.ts/0
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50
<script lang="ts"> import { page } from "$app/stores"; import { getHref } from "$lib/utils/getHref"; import PaginationArrow from "./PaginationArrow.svelte"; export let classNames = ""; export let numItemsPerPage: number; export let numTotalItems: number; const ELLIPSIS_IDX = -1 as const; $: numTotalPages = M...
chat-ui/src/lib/components/Pagination.svelte/0
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51
<script lang="ts"> import type { Message } from "$lib/types/Message"; import { createEventDispatcher, onDestroy, tick } from "svelte"; import CarbonSendAltFilled from "~icons/carbon/send-alt-filled"; import CarbonExport from "~icons/carbon/export"; import CarbonStopFilledAlt from "~icons/carbon/stop-filled-alt"; ...
chat-ui/src/lib/components/chat/ChatWindow.svelte/0
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52
// Shouldn't be needed if we dove into sveltekit internals, see https://github.com/huggingface/chat-ui/pull/88#issuecomment-1523173850 import { setTimeout } from "node:timers/promises"; import { collections } from "./database"; let closed = false; process.on("SIGINT", () => { closed = true; }); export let abortedGe...
chat-ui/src/lib/server/abortedGenerations.ts/0
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53
import { error } from "@sveltejs/kit"; import { collections } from "../database"; import type { Conversation } from "$lib/types/Conversation"; import type { SharedConversation } from "$lib/types/SharedConversation"; export async function downloadFile( sha256: string, convId: Conversation["_id"] | SharedConversation[...
chat-ui/src/lib/server/files/downloadFile.ts/0
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54
import { writable } from "svelte/store"; export const ERROR_MESSAGES = { default: "Oops, something went wrong.", authOnly: "You have to be logged in.", rateLimited: "You are sending too many messages. Try again later.", }; export const error = writable<string | null>(null);
chat-ui/src/lib/stores/errors.ts/0
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55
import type { BackendModel } from "$lib/server/models"; export type Model = Pick< BackendModel, | "id" | "name" | "displayName" | "websiteUrl" | "datasetName" | "promptExamples" | "parameters" | "description" | "logoUrl" | "modelUrl" | "datasetUrl" | "preprompt" | "multimodal" | "unlisted" >;
chat-ui/src/lib/types/Model.ts/0
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56
export function deepestChild(el: HTMLElement): HTMLElement { if (el.lastElementChild && el.lastElementChild.nodeType !== Node.TEXT_NODE) { return deepestChild(el.lastElementChild as HTMLElement); } return el; }
chat-ui/src/lib/utils/deepestChild.ts/0
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57
import type { Message } from "$lib/types/Message"; import type { LegacyParamatersTemplateInput } from "$lib/types/Template"; import Handlebars from "handlebars"; Handlebars.registerHelper("ifUser", function (this: Pick<Message, "from" | "content">, options) { if (this.from == "user") return options.fn(this); }); Han...
chat-ui/src/lib/utils/template.ts/0
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58
<script lang="ts"> import { goto } from "$app/navigation"; import { base } from "$app/paths"; import { PUBLIC_APP_NAME } from "$env/static/public"; import ChatWindow from "$lib/components/chat/ChatWindow.svelte"; import { ERROR_MESSAGES, error } from "$lib/stores/errors"; import { pendingMessage } from "$lib/stor...
chat-ui/src/routes/+page.svelte/0
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59
import { MESSAGES_BEFORE_LOGIN } from "$env/static/private"; import { authCondition, requiresUser } from "$lib/server/auth"; import { collections } from "$lib/server/database"; import { models } from "$lib/server/models"; import { ERROR_MESSAGES } from "$lib/stores/errors"; import type { Message } from "$lib/types/Mess...
chat-ui/src/routes/conversation/[id]/+server.ts/0
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60
<script lang="ts"> import { PUBLIC_APP_COLOR } from "$env/static/public"; import { isHuggingChat } from "$lib/utils/isHuggingChat"; export let name: string; export let logoUrl: string | undefined; import logo from "../../../../../static/huggingchat/logo.svg?raw"; </script> <div class=" flex h-[648px] w-full fle...
chat-ui/src/routes/models/[...model]/thumbnail.png/ModelThumbnail.svelte/0
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61
<script lang="ts"> import type { ActionData, PageData } from "./$types"; import AssistantSettings from "$lib/components/AssistantSettings.svelte"; export let data: PageData; export let form: ActionData; </script> <AssistantSettings bind:form models={data.models} />
chat-ui/src/routes/settings/(nav)/assistants/new/+page@settings.svelte/0
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62
{ "background_color": "#ffffff", "name": "HuggingChat", "short_name": "HuggingChat", "display": "standalone", "start_url": "/chat", "icons": [ { "src": "/chat/huggingchat/icon-128x128.png", "sizes": "128x128", "type": "image/png" }, { "src": "/chat/huggingchat/icon-256x256.png", "sizes": "256...
chat-ui/static/huggingchat/manifest.json/0
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63
# This first_section was backported from nginx loading_datasets: loading share_dataset: share quicktour: quickstart dataset_streaming: stream torch_tensorflow: use_dataset splits: loading#slice-splits processing: process faiss_and_ea: faiss_es features: about_dataset_features using_metrics: how_to_metrics exploring: ac...
datasets/docs/source/_redirects.yml/0
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64
# Create a dataset card Each dataset should have a dataset card to promote responsible usage and inform users of any potential biases within the dataset. This idea was inspired by the Model Cards proposed by [Mitchell, 2018](https://arxiv.org/abs/1810.03993). Dataset cards help users understand a dataset's contents, t...
datasets/docs/source/dataset_card.mdx/0
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65
# Load Your data can be stored in various places; they can be on your local machine's disk, in a Github repository, and in in-memory data structures like Python dictionaries and Pandas DataFrames. Wherever a dataset is stored, 🤗 Datasets can help you load it. This guide will show you how to load a dataset from: - T...
datasets/docs/source/loading.mdx/0
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66
# Stream Dataset streaming lets you work with a dataset without downloading it. The data is streamed as you iterate over the dataset. This is especially helpful when: - You don't want to wait for an extremely large dataset to download. - The dataset size exceeds the amount of available disk space on your computer. - ...
datasets/docs/source/stream.mdx/0
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67
# 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/bleu/bleu.py/0
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68
# Metric Card for CUAD ## Metric description This metric wraps the official scoring script for version 1 of the [Contract Understanding Atticus Dataset (CUAD)](https://huggingface.co/datasets/cuad), which is a corpus of more than 13,000 labels in 510 commercial legal contracts that have been manually labeled to ident...
datasets/metrics/cuad/README.md/0
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69
# Copyright 2022 The HuggingFace Datasets Authors and the current dataset script contributor. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2....
datasets/metrics/mae/mae.py/0
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70
# Copyright 2022 The HuggingFace Datasets Authors and the current dataset script contributor. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2....
datasets/metrics/perplexity/perplexity.py/0
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71
# Copyright 2021 The HuggingFace Datasets Authors and the current dataset script contributor. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2....
datasets/metrics/spearmanr/spearmanr.py/0
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72
# Metric Card for XNLI ## Metric description The XNLI metric allows to evaluate a model's score on the [XNLI dataset](https://huggingface.co/datasets/xnli), which is a subset of a few thousand examples from the [MNLI dataset](https://huggingface.co/datasets/glue/viewer/mnli) that have been translated into a 14 differ...
datasets/metrics/xnli/README.md/0
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73
#!/usr/bin/env python from argparse import ArgumentParser from datasets.commands.convert import ConvertCommand from datasets.commands.dummy_data import DummyDataCommand from datasets.commands.env import EnvironmentCommand from datasets.commands.run_beam import RunBeamCommand from datasets.commands.test import TestComm...
datasets/src/datasets/commands/datasets_cli.py/0
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74
import os from dataclasses import dataclass, field from io import BytesIO from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union import numpy as np import pyarrow as pa from .. import config from ..download.download_config import DownloadConfig from ..download.streaming_download_manager import xopen, ...
datasets/src/datasets/features/audio.py/0
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75
# 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/src/datasets/inspect.py/0
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76
# 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/splits.py/0
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77
import os from apache_beam.io.filesystems import FileSystems from apache_beam.pipeline import Pipeline from .logging import get_logger CHUNK_SIZE = 2 << 20 # 2mb logger = get_logger(__name__) class BeamPipeline(Pipeline): """Wrapper over `apache_beam.pipeline.Pipeline` for convenience""" def is_local(se...
datasets/src/datasets/utils/beam_utils.py/0
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78
{ "language": [ "found", "crowdsourced", "expert-generated", "machine-generated", "other" ], "annotations": [ "found", "crowdsourced", "expert-generated", "machine-generated", "no-annotation", "other" ] }
datasets/src/datasets/utils/resources/creators.json/0
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## Add Dummy data test **Important** In order to pass the `load_dataset_<dataset_name>` test, dummy data is required for all possible config names. First we distinguish between datasets scripts that - A) have no config class and - B) have a config class For A) the dummy data folder structure, will always look as fol...
datasets/tests/README.md/0
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80
import os import random import tempfile import unittest import numpy as np import pandas as pd import pyarrow as pa import pytest from absl.testing import parameterized import datasets from datasets.arrow_writer import ArrowWriter from datasets.features import Array2D, Array3D, Array4D, Array5D, Value from datasets.f...
datasets/tests/features/test_array_xd.py/0
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import pytest from datasets import Dataset, DatasetDict, Features, NamedSplit, Value from datasets.io.text import TextDatasetReader from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases def _check_text_dataset(dataset, expected_features): assert isinstance(dataset, Dataset) ...
datasets/tests/io/test_text.py/0
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82
import copy import os from pathlib import Path from typing import List from unittest.mock import patch import fsspec import pytest from fsspec.registry import _registry as _fsspec_registry from fsspec.spec import AbstractFileSystem from datasets.data_files import ( DataFilesDict, DataFilesList, DataFilesP...
datasets/tests/test_data_files.py/0
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83
import os from pathlib import Path import pytest from datasets.inspect import ( get_dataset_config_info, get_dataset_config_names, get_dataset_default_config_name, get_dataset_infos, get_dataset_split_names, inspect_dataset, inspect_metric, ) from datasets.packaged_modules.csv import csv ...
datasets/tests/test_inspect.py/0
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84
from copy import deepcopy from unittest.case import TestCase import pytest from datasets.arrow_dataset import Dataset from datasets.features import Audio, ClassLabel, Features, Image, Sequence, Value from datasets.info import DatasetInfo from datasets.tasks import ( AudioClassification, AutomaticSpeechRecogni...
datasets/tests/test_tasks.py/0
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# Setup [[setup]] After all this information, it's time to get started. We're going to do two things: 1. **Create your Hugging Face account** if it's not already done 2. **Sign up to Discord and introduce yourself** (don't be shy 🤗) ### Let's create my Hugging Face account (If it's not already done) create an acco...
deep-rl-class/units/en/unit0/setup.mdx/0
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# Conclusion [[conclusion]] Congrats on finishing this chapter! There was a lot of information. And congrats on finishing the tutorials. You’ve just implemented your first RL agent from scratch and shared it on the Hub 🥳. Implementing from scratch when you study a new architecture **is important to understand how it...
deep-rl-class/units/en/unit2/conclusion.mdx/0
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# The Deep Q-Network (DQN) [[deep-q-network]] This is the architecture of our Deep Q-Learning network: <img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit4/deep-q-network.jpg" alt="Deep Q Network"/> As input, we take a **stack of 4 frames** passed through the netwo...
deep-rl-class/units/en/unit3/deep-q-network.mdx/0
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# Bonus: Learn to create your own environments with Unity and MLAgents **You can create your own reinforcement learning environments with Unity and MLAgents**. Using a game engine such as Unity can be intimidating at first, but here are the steps you can take to learn smoothly. ## Step 1: Know how to use Unity - The...
deep-rl-class/units/en/unit5/bonus.mdx/0
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# Additional Readings [[additional-readings]] ## An introduction to multi-agents - [Multi-agent reinforcement learning: An overview](https://www.dcsc.tudelft.nl/~bdeschutter/pub/rep/10_003.pdf) - [Multiagent Reinforcement Learning, Marc Lanctot](https://rlss.inria.fr/files/2019/07/RLSS_Multiagent.pdf) - [Example of ...
deep-rl-class/units/en/unit7/additional-readings.mdx/0
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# The intuition behind PPO [[the-intuition-behind-ppo]] The idea with Proximal Policy Optimization (PPO) is that we want to improve the training stability of the policy by limiting the change you make to the policy at each training epoch: **we want to avoid having too large of a policy update.** For two reasons: - W...
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# Language models in RL ## LMs encode useful knowledge for agents **Language models** (LMs) can exhibit impressive abilities when manipulating text such as question-answering or even step-by-step reasoning. Additionally, their training on massive text corpora allowed them to **encode various types of knowledge includi...
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cff-version: 1.2.0 title: 'Diffusers: State-of-the-art diffusion models' message: >- If you use this software, please cite it using the metadata from this file. type: software authors: - given-names: Patrick family-names: von Platen - given-names: Suraj family-names: Patil - given-names: Anton fam...
diffusers/CITATION.cff/0
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import argparse import sys sys.path.append(".") from base_classes import TextToImageBenchmark, TurboTextToImageBenchmark # noqa: E402 ALL_T2I_CKPTS = [ "runwayml/stable-diffusion-v1-5", "segmind/SSD-1B", "stabilityai/stable-diffusion-xl-base-1.0", "kandinsky-community/kandinsky-2-2-decoder", "w...
diffusers/benchmarks/benchmark_text_to_image.py/0
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diffusers/docs/source/en/api/models/controlnet.md/0
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diffusers/docs/source/en/api/pipelines/kandinsky3.md/0
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diffusers/docs/source/en/api/pipelines/stable_diffusion/upscale.md/0
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diffusers/docs/source/en/api/schedulers/singlestep_dpm_solver.md/0
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diffusers/docs/source/en/optimization/fp16.md/0
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diffusers/docs/source/en/training/ddpo.md/0
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diffusers/docs/source/en/tutorials/fast_diffusion.md/0
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diffusers/docs/source/en/using-diffusers/inference_with_lcm.md/0
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diffusers/docs/source/en/using-diffusers/schedulers.md/0
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diffusers/docs/source/ja/stable_diffusion.md/0
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diffusers/docs/source/ko/optimization/torch2.0.md/0
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diffusers/docs/source/ko/tutorials/basic_training.md/0
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diffusers/docs/source/ko/using-diffusers/reusing_seeds.md/0
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diffusers/docs/source/zh/stable_diffusion.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 applicabl...
diffusers/examples/community/dps_pipeline.py/0
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from typing import Union import torch from PIL import Image from torchvision import transforms as tfms from tqdm.auto import tqdm from transformers import CLIPTextModel, CLIPTokenizer from diffusers import ( AutoencoderKL, DDIMScheduler, DiffusionPipeline, LMSDiscreteScheduler, PNDMScheduler, ...
diffusers/examples/community/magic_mix.py/0
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# Copyright 2024 Jake Babbidge, TencentARC 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/examples/community/pipeline_stable_diffusion_xl_controlnet_adapter_inpaint.py/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.py/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/dreambooth/train_dreambooth.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_decoder.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/examples/research_projects/controlnetxs/controlnetxs.py/0
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import argparse import intel_extension_for_pytorch as ipex import torch from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline parser = argparse.ArgumentParser("Stable Diffusion script with intel optimization", add_help=False) parser.add_argument("--dpm", action="store_true", help="Enable DPMSol...
diffusers/examples/research_projects/intel_opts/inference_bf16.py/0
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import argparse import copy import itertools import logging import math import os import random from pathlib import Path import numpy as np import torch import torch.nn.functional as F import torch.utils.checkpoint from accelerate import Accelerator from accelerate.logging import get_logger from accelerate.utils impor...
diffusers/examples/research_projects/multi_subject_dreambooth_inpainting/train_multi_subject_dreambooth_inpainting.py/0
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# T2I-Adapter training example for Stable Diffusion XL (SDXL) The `train_t2i_adapter_sdxl.py` script shows how to implement the [T2I-Adapter training procedure](https://hf.co/papers/2302.08453) for [Stable Diffusion XL](https://huggingface.co/papers/2307.01952). ## Running locally with PyTorch ### Installing the dep...
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import torch.nn as nn from torchvision.models import efficientnet_v2_l, efficientnet_v2_s from diffusers.configuration_utils import ConfigMixin, register_to_config from diffusers.models.modeling_utils import ModelMixin class EfficientNetEncoder(ModelMixin, ConfigMixin): @register_to_config def __init__(self,...
diffusers/examples/wuerstchen/text_to_image/modeling_efficient_net_encoder.py/0
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import argparse import json import torch from diffusers import AutoencoderKL, DDPMPipeline, DDPMScheduler, UNet2DModel, VQModel def shave_segments(path, n_shave_prefix_segments=1): """ Removes segments. Positive values shave the first segments, negative shave the last segments. """ if n_shave_prefix...
diffusers/scripts/convert_ddpm_original_checkpoint_to_diffusers.py/0
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#!/usr/bin/env python3 import argparse import os import jax as jnp import numpy as onp import torch import torch.nn as nn from music_spectrogram_diffusion import inference from t5x import checkpoints from diffusers import DDPMScheduler, OnnxRuntimeModel, SpectrogramDiffusionPipeline from diffusers.pipelines.spectrogr...
diffusers/scripts/convert_music_spectrogram_to_diffusers.py/0
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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
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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/commands/fp16_safetensors.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/loaders/single_file.py/0
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# Copyright 2024 Ollin Boer Bohan 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/models/autoencoders/autoencoder_tiny.py/0
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from ..utils import deprecate from .transformers.prior_transformer import PriorTransformer, PriorTransformerOutput class PriorTransformerOutput(PriorTransformerOutput): deprecation_message = "Importing `PriorTransformerOutput` from `diffusers.models.prior_transformer` is deprecated and this will be removed in a f...
diffusers/src/diffusers/models/prior_transformer.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/unet_2d_condition.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/models/unets/uvit_2d.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/audioldm/pipeline_audioldm.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/deprecated/audio_diffusion/pipeline_audio_diffusion.py/0
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import inspect from typing import Callable, List, Optional, Union import numpy as np import PIL.Image import torch from transformers import CLIPImageProcessor, CLIPTokenizer from ....configuration_utils import FrozenDict from ....schedulers import DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler from ....utils impo...
diffusers/src/diffusers/pipelines/deprecated/stable_diffusion_variants/pipeline_onnx_stable_diffusion_inpaint_legacy.py/0
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# Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) # William Peebles and Saining Xie # # Copyright (c) 2021 OpenAI # MIT License # # 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 wi...
diffusers/src/diffusers/pipelines/dit/pipeline_dit.py/0
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# 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/ledits_pp/pipeline_leditspp_stable_diffusion_xl.py/0
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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 SemanticStableDiffusionPipelineOutput(BaseOutput): """ Output class for Stable Diffusion pipelines. Args: images (`List[PIL.Image.Image...
diffusers/src/diffusers/pipelines/semantic_stable_diffusion/pipeline_output.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/stable_diffusion/pipeline_flax_stable_diffusion_img2img.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/stable_diffusion/pipeline_stable_unclip_img2img.py/0
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