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import pytest @pytest.fixture(scope="module") def flash_santacoder_handle(launcher): with launcher("bigcode/santacoder") as handle: yield handle @pytest.fixture(scope="module") async def flash_santacoder(flash_santacoder_handle): await flash_santacoder_handle.health(300) return flash_santacoder_...
text-generation-inference/integration-tests/models/test_flash_santacoder.py/0
{ "file_path": "text-generation-inference/integration-tests/models/test_flash_santacoder.py", "repo_id": "text-generation-inference", "token_count": 403 }
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import pytest @pytest.fixture(scope="module") def mt0_base_handle(launcher): with launcher("bigscience/mt0-base") as handle: yield handle @pytest.fixture(scope="module") async def mt0_base(mt0_base_handle): await mt0_base_handle.health(300) return mt0_base_handle.client @pytest.mark.release @p...
text-generation-inference/integration-tests/models/test_mt0_base.py/0
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use std::error::Error; use vergen::EmitBuilder; fn main() -> Result<(), Box<dyn Error>> { // Emit cargo and rustc compile time values EmitBuilder::builder().all_cargo().all_rustc().emit()?; // Try to get the git sha from the local git repository if EmitBuilder::builder() .fail_on_error() ...
text-generation-inference/launcher/build.rs/0
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312
{ stdenv, dockerTools, cacert, text-generation-inference, stream ? false, }: let build = if stream then dockerTools.streamLayeredImage else dockerTools.buildLayeredImage; in build { name = "tgi-docker"; tag = "latest"; compressor = "zstd"; config = { EntryPoint = [ "${text-generation-inference}...
text-generation-inference/nix/docker.nix/0
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313
use axum::{extract::Request, middleware::Next, response::Response}; use opentelemetry::sdk::propagation::TraceContextPropagator; use opentelemetry::sdk::trace; use opentelemetry::sdk::trace::Sampler; use opentelemetry::sdk::Resource; use opentelemetry::trace::{SpanContext, SpanId, TraceContextExt, TraceFlags, TraceId};...
text-generation-inference/router/src/logging.rs/0
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314
selective_scan_commit := 2a3704fd47ba817b415627b06fd796b971fdc137 causal-conv1d: rm -rf causal-conv1d git clone https://github.com/Dao-AILab/causal-conv1d.git build-causal-conv1d: causal-conv1d cd causal-conv1d/ && git checkout v1.1.1 # known latest working version tag cd causal-conv1d/ && CAUSAL_CONV1D_FORCE_BUI...
text-generation-inference/server/Makefile-selective-scan/0
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315
// Adapted from turboderp exllama: https://github.com/turboderp/exllama #include <torch/extension.h> #include <c10/cuda/CUDAGuard.h> #include <ATen/cuda/CUDAContext.h> #include <cuda_runtime.h> #include <cuda_fp16.h> #include <cstdint> #include <cstdio> #include "util.cuh" #include "tuning.h" #include "cuda_buffers.cu...
text-generation-inference/server/exllama_kernels/exllama_kernels/exllama_ext.cpp/0
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#ifndef _qdq_2_cuh #define _qdq_2_cuh #include "qdq_util.cuh" #include "../../config.h" #if QMODE_2BIT == 1 // Permutation: // // ffddbb99 77553311 eeccaa88 66442200 __forceinline__ __device__ void shuffle_2bit_16 ( uint32_t* q, int stride ) { uint32_t qa = q[0]; uint32_t qb = 0; #pragma unrol...
text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/quant/qdq_2.cuh/0
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317
from text_generation_server.utils.import_utils import SYSTEM if SYSTEM == "ipex": from .ipex import WQLinear elif SYSTEM == "cuda": from .cuda import WQLinear __all__ = ["WQLinear"]
text-generation-inference/server/text_generation_server/layers/awq/quantize/__init__.py/0
{ "file_path": "text-generation-inference/server/text_generation_server/layers/awq/quantize/__init__.py", "repo_id": "text-generation-inference", "token_count": 71 }
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from text_generation_server.layers.gptq import GPTQWeight import torch from exllama_kernels import make_q4, q4_matmul, prepare_buffers, set_tuning_params # Dummy tensor to pass instead of g_idx since there is no way to pass "None" to a C++ extension none_tensor = torch.empty((1, 1), device="meta") def ext_make_q4(qw...
text-generation-inference/server/text_generation_server/layers/gptq/exllama.py/0
{ "file_path": "text-generation-inference/server/text_generation_server/layers/gptq/exllama.py", "repo_id": "text-generation-inference", "token_count": 1888 }
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from typing import Optional, Protocol, runtime_checkable import torch import torch.nn as nn from loguru import logger from transformers.activations import ACT2FN from text_generation_server.layers import ( TensorParallelColumnLinear, TensorParallelRowLinear, ) from text_generation_server.layers.fp8 import Hyb...
text-generation-inference/server/text_generation_server/layers/moe/__init__.py/0
{ "file_path": "text-generation-inference/server/text_generation_server/layers/moe/__init__.py", "repo_id": "text-generation-inference", "token_count": 4641 }
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# coding=utf-8 # Copyright 2023, 2024 DeepSeek-AI and 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...
text-generation-inference/server/text_generation_server/models/custom_modeling/flash_deepseek_v2_modeling.py/0
{ "file_path": "text-generation-inference/server/text_generation_server/models/custom_modeling/flash_deepseek_v2_modeling.py", "repo_id": "text-generation-inference", "token_count": 11480 }
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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...
text-generation-inference/server/text_generation_server/models/custom_modeling/mllama.py/0
{ "file_path": "text-generation-inference/server/text_generation_server/models/custom_modeling/mllama.py", "repo_id": "text-generation-inference", "token_count": 18370 }
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import torch import numpy as np from typing import Iterable, Optional, Tuple, List, Dict from text_generation_server.pb.generate_pb2 import Request from io import BytesIO from PIL import Image from dataclasses import dataclass from opentelemetry import trace from transformers import ( PreTrainedTokenizerBase, ) ...
text-generation-inference/server/text_generation_server/models/mllama_causal_lm.py/0
{ "file_path": "text-generation-inference/server/text_generation_server/models/mllama_causal_lm.py", "repo_id": "text-generation-inference", "token_count": 7966 }
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import torch from loguru import logger import os import importlib.util def is_ipex_available(): return importlib.util.find_spec("intel_extension_for_pytorch") is not None def get_cuda_free_memory(device, memory_fraction): total_free_memory, _ = torch.cuda.mem_get_info(device) total_gpu_memory = torch....
text-generation-inference/server/text_generation_server/utils/import_utils.py/0
{ "file_path": "text-generation-inference/server/text_generation_server/utils/import_utils.py", "repo_id": "text-generation-inference", "token_count": 893 }
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import subprocess import argparse import ast import json import os TEMPLATE = """ # Supported Models Text Generation Inference enables serving optimized models. The following sections list which models (VLMs & LLMs) are supported. SUPPORTED_MODELS If the above list lacks the model you would like to serve, dependin...
text-generation-inference/update_doc.py/0
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325
extern crate napi_build; fn main() { napi_build::setup(); }
tokenizers/bindings/node/build.rs/0
{ "file_path": "tokenizers/bindings/node/build.rs", "repo_id": "tokenizers", "token_count": 26 }
326
// import { promisify } from 'util' import { BPE, Tokenizer, mergeEncodings, slice } from '../../' describe('slice', () => { const text = 'My name is John 👋' const sliceText = slice.bind({}, text) it('returns the full text when no params', () => { const sliced = sliceText() expect(sliced).toEqual(text...
tokenizers/bindings/node/lib/bindings/utils.test.ts/0
{ "file_path": "tokenizers/bindings/node/lib/bindings/utils.test.ts", "repo_id": "tokenizers", "token_count": 1866 }
327
{ "name": "tokenizers-linux-arm64-musl", "version": "0.13.4-rc1", "os": [ "linux" ], "cpu": [ "arm64" ], "main": "tokenizers.linux-arm64-musl.node", "files": [ "tokenizers.linux-arm64-musl.node" ], "description": "Tokenizers platform specific bindings", "keywords": [ "napi-rs", ...
tokenizers/bindings/node/npm/linux-arm64-musl/package.json/0
{ "file_path": "tokenizers/bindings/node/npm/linux-arm64-musl/package.json", "repo_id": "tokenizers", "token_count": 291 }
328
#![deny(clippy::all)] pub const VERSION: &str = env!("CARGO_PKG_VERSION"); mod arc_rwlock_serde; pub mod decoders; pub mod encoding; pub mod models; pub mod normalizers; pub mod pre_tokenizers; pub mod processors; pub mod tasks; pub mod tokenizer; pub mod trainers; pub mod utils;
tokenizers/bindings/node/src/lib.rs/0
{ "file_path": "tokenizers/bindings/node/src/lib.rs", "repo_id": "tokenizers", "token_count": 102 }
329
# Changelog All notable changes to this project will be documented in this file. The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/), and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html). ## [0.13.2] - [#1096] Python 3.11 support ## [0.13.1] - [#1072]...
tokenizers/bindings/python/CHANGELOG.md/0
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330
# Generated content DO NOT EDIT class DecodeStream: """ Class needed for streaming decode """ def __init__(self, ids=None, skip_special_tokens=False): pass class Decoder: """ Base class for all decoders This class is not supposed to be instantiated directly. Instead, any implement...
tokenizers/bindings/python/py_src/tokenizers/decoders/__init__.pyi/0
{ "file_path": "tokenizers/bindings/python/py_src/tokenizers/decoders/__init__.pyi", "repo_id": "tokenizers", "token_count": 3243 }
331
from .visualizer import Annotation, EncodingVisualizer
tokenizers/bindings/python/py_src/tokenizers/tools/__init__.py/0
{ "file_path": "tokenizers/bindings/python/py_src/tokenizers/tools/__init__.py", "repo_id": "tokenizers", "token_count": 13 }
332
use pyo3::exceptions::PyException; use pyo3::types::*; use pyo3::{exceptions, prelude::*}; use std::sync::{Arc, RwLock}; use crate::error::ToPyResult; use crate::utils::{PyNormalizedString, PyNormalizedStringRefMut, PyPattern}; use serde::ser::SerializeStruct; use serde::{Deserialize, Deserializer, Serialize, Serializ...
tokenizers/bindings/python/src/normalizers.rs/0
{ "file_path": "tokenizers/bindings/python/src/normalizers.rs", "repo_id": "tokenizers", "token_count": 14563 }
333
import json import pickle import pytest from tokenizers.decoders import ( CTC, BPEDecoder, ByteLevel, Decoder, Metaspace, Sequence, WordPiece, ByteFallback, Replace, Strip, Fuse, ) class TestByteLevel: def test_instantiate(self): assert ByteLevel() is not None...
tokenizers/bindings/python/tests/bindings/test_decoders.py/0
{ "file_path": "tokenizers/bindings/python/tests/bindings/test_decoders.py", "repo_id": "tokenizers", "token_count": 3527 }
334
from tokenizers import CharBPETokenizer from ..utils import data_dir, multiprocessing_with_parallelism, openai_files class TestCharBPETokenizer: def test_basic_encode(self, openai_files): tokenizer = CharBPETokenizer.from_file(openai_files["vocab"], openai_files["merges"]) output = tokenizer.enc...
tokenizers/bindings/python/tests/implementations/test_char_bpe.py/0
{ "file_path": "tokenizers/bindings/python/tests/implementations/test_char_bpe.py", "repo_id": "tokenizers", "token_count": 1094 }
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# Tokenizer <tokenizerslangcontent> <python> ## Tokenizer [[autodoc]] tokenizers.Tokenizer - all - decoder - model - normalizer - padding - post_processor - pre_tokenizer - truncation </python> <rust> The Rust API Reference is available directly on the [Docs.rs](https://docs.rs/tokeniz...
tokenizers/docs/source-doc-builder/api/tokenizer.mdx/0
{ "file_path": "tokenizers/docs/source-doc-builder/api/tokenizer.mdx", "repo_id": "tokenizers", "token_count": 156 }
336
.highlight .c1, .highlight .sd{ color: #999 } .highlight .nn, .highlight .k, .highlight .s1, .highlight .nb, .highlight .bp, .highlight .kc, .highlight .kt { color: #FB8D68; } .highlight .kn, .highlight .nv, .highlight .s2, .highlight .ow, .highlight .kd, .highlight .kr, .highlight .s { color: #6670FF; }...
tokenizers/docs/source/_static/css/code-snippets.css/0
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337
Quicktour ==================================================================================================== Let's have a quick look at the 🤗 Tokenizers library features. The library provides an implementation of today's most used tokenizers that is both easy to use and blazing fast. .. only:: python It can b...
tokenizers/docs/source/quicktour.rst/0
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338
{ "name": "create-wasm-app", "version": "0.1.0", "description": "create an app to consume rust-generated wasm packages", "main": "index.js", "bin": { "create-wasm-app": ".bin/create-wasm-app.js" }, "scripts": { "build": "webpack --config webpack.config.js", "start": "...
tokenizers/tokenizers/examples/unstable_wasm/www/package.json/0
{ "file_path": "tokenizers/tokenizers/examples/unstable_wasm/www/package.json", "repo_id": "tokenizers", "token_count": 516 }
339
use super::Pair; use ahash::AHashMap; use dary_heap::QuaternaryHeap; use rand::{rng, Rng}; use std::cmp::Ordering; #[derive(Debug, Eq)] struct Merge { pos: usize, rank: u32, new_id: u32, } impl PartialEq for Merge { fn eq(&self, other: &Self) -> bool { self.rank == other.rank && self.pos == ot...
tokenizers/tokenizers/src/models/bpe/word.rs/0
{ "file_path": "tokenizers/tokenizers/src/models/bpe/word.rs", "repo_id": "tokenizers", "token_count": 6448 }
340
pub mod bert; pub mod byte_level; pub mod precompiled; pub mod prepend; pub mod replace; pub mod strip; pub mod unicode; pub mod utils; pub use crate::normalizers::bert::BertNormalizer; pub use crate::normalizers::byte_level::ByteLevel; pub use crate::normalizers::precompiled::Precompiled; pub use crate::normalizers::p...
tokenizers/tokenizers/src/normalizers/mod.rs/0
{ "file_path": "tokenizers/tokenizers/src/normalizers/mod.rs", "repo_id": "tokenizers", "token_count": 5898 }
341
use crate::utils::SysRegex; use serde::{Deserialize, Deserializer, Serialize}; use crate::tokenizer::{ pattern::Invert, PreTokenizedString, PreTokenizer, Result, SplitDelimiterBehavior, }; /// Represents the different patterns that `Split` can use #[derive(Debug, Clone, PartialEq, Serialize, Deserialize, Eq)] pub...
tokenizers/tokenizers/src/pre_tokenizers/split.rs/0
{ "file_path": "tokenizers/tokenizers/src/pre_tokenizers/split.rs", "repo_id": "tokenizers", "token_count": 4042 }
342
use std::marker::PhantomData; use serde::{ self, de::{Error, MapAccess, Visitor}, ser::SerializeStruct, Deserialize, Deserializer, Serialize, Serializer, }; use super::{added_vocabulary::AddedTokenWithId, TokenizerImpl}; use crate::{Decoder, Model, Normalizer, PostProcessor, PreTokenizer, TokenizerBui...
tokenizers/tokenizers/src/tokenizer/serialization.rs/0
{ "file_path": "tokenizers/tokenizers/src/tokenizer/serialization.rs", "repo_id": "tokenizers", "token_count": 3685 }
343
mod common; use common::*; use tokenizers::decoders::byte_level::ByteLevel; use tokenizers::decoders::DecoderWrapper; use tokenizers::models::bpe::BPE; use tokenizers::models::wordlevel::WordLevel; use tokenizers::models::wordpiece::WordPiece; use tokenizers::models::ModelWrapper; use tokenizers::normalizers::bert::Be...
tokenizers/tokenizers/tests/serialization.rs/0
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344
# Accessing Private/Gated Models <Tip> Due to the possibility of leaking access tokens to users of your website or web application, we only support accessing private/gated models from server-side environments (e.g., Node.js) that have access to the process' environment variables. </Tip> ## Step 1: Generating a Use...
transformers.js/docs/source/guides/private.md/0
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345
import React from 'react' import ReactDOM from 'react-dom/client' import App from './App.jsx' import './index.css' ReactDOM.createRoot(document.getElementById('root')).render( <React.StrictMode> <App /> </React.StrictMode>, )
transformers.js/examples/cross-encoder/src/main.jsx/0
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346
* { box-sizing: border-box; padding: 0; margin: 0; font-family: sans-serif; } html, body { height: 100%; } body { padding: 16px 32px; } body, #container, #upload-button { display: flex; flex-direction: column; justify-content: center; align-items: center; } h1 { text-align: center; } #contain...
transformers.js/examples/depth-anything-client/style.css/0
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347
{ "name": "extension", "version": "0.0.1", "description": "Transformers.js | Sample browser extension", "scripts": { "build": "webpack", "dev": "webpack --watch" }, "type": "module", "author": "Xenova", "license": "MIT", "devDependencies": { "copy-webpack-plugin": "^11.0.0", "html-webp...
transformers.js/examples/extension/package.json/0
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348
import { useState, useRef } from 'react'; const EXAMPLE_URL = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/beetle.png'; const ImageInput = ({ onImageChange, ...props }) => { const [imagePreview, setImagePreview] = useState(null); const fileInputRef = useRef(null); const readF...
transformers.js/examples/florence2-webgpu/src/components/ImageInput.jsx/0
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349
import './globals.css' import { Inter } from 'next/font/google' const inter = Inter({ subsets: ['latin'] }) export const metadata = { title: 'Create Next App', description: 'Generated by create next app', } export default function RootLayout({ children }) { return ( <html lang="en"> <body className={...
transformers.js/examples/next-client/src/app/layout.js/0
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350
// Create a custom request handler for the /classify route. // For more information, see https://nextjs.org/docs/app/building-your-application/routing/router-handlers import { NextResponse } from 'next/server' import PipelineSingleton from './pipeline.js'; export async function GET(request) { const text = request...
transformers.js/examples/next-server/src/app/classify/route.js/0
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#root { max-width: 1280px; margin: 0 auto; padding: 2rem; text-align: center; } .language-container { display: flex; gap: 20px; } .textbox-container { display: flex; justify-content: center; gap: 20px; width: 800px; } .textbox-container>textarea, .language-selector { width: 50%; } .language-se...
transformers.js/examples/react-translator/src/App.css/0
{ "file_path": "transformers.js/examples/react-translator/src/App.css", "repo_id": "transformers.js", "token_count": 383 }
352
* { box-sizing: border-box; padding: 0; margin: 0; font-family: sans-serif; } html, body { height: 100%; } body { padding: 16px 32px; } body, #container, #upload-button { display: flex; flex-direction: column; justify-content: center; align-items: center; } h1, h3 { text-...
transformers.js/examples/segment-anything-client/index.css/0
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This is a [Next.js](https://nextjs.org/) project bootstrapped with [`create-next-app`](https://github.com/vercel/next.js/tree/canary/packages/create-next-app). ## Getting Started First, run the development server: ```bash npm run dev # or yarn dev # or pnpm dev ``` Open [http://localhost:3000](http://localhost:3000...
transformers.js/examples/semantic-image-search-client/README.md/0
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import { env, AutoTokenizer, CLIPTextModelWithProjection } from '@xenova/transformers'; import { getCachedFile, getCachedJSON } from './utils.js'; const EMBED_DIM = 512; // Skip local model check env.allowLocalModels = false; class ApplicationSingleton { static model_id = 'Xenova/clip-vit-base-patch16'; sta...
transformers.js/examples/semantic-image-search-client/src/app/worker.js/0
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import Image from 'next/image' import { blurHashToDataURL } from '../utils.js' export function ImageGrid({ images, setCurrentImage }) { return ( <div className="columns-2 gap-4 sm:columns-3 xl:columns-4 2xl:columns-5"> {images && images.map(({ photo_id, photo_url...
transformers.js/examples/semantic-image-search/src/app/components/ImageGrid.jsx/0
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import React, { useState, useEffect, useRef } from 'react'; import AudioPlayer from './components/AudioPlayer'; import Progress from './components/Progress'; import { SPEAKERS, DEFAULT_SPEAKER } from './constants'; const App = () => { // Model loading const [ready, setReady] = useState(null); const [disabled, ...
transformers.js/examples/text-to-speech-client/src/App.jsx/0
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357
{ "name": "video-object-detection", "version": "0.0.0", "lockfileVersion": 3, "requires": true, "packages": { "": { "name": "video-object-detection", "version": "0.0.0", "dependencies": { "@xenova/transformers": "^2.15.0" }, "devDependencies": { "vite": "^5.1....
transformers.js/examples/video-object-detection/package-lock.json/0
{ "file_path": "transformers.js/examples/video-object-detection/package-lock.json", "repo_id": "transformers.js", "token_count": 32066 }
358
import './style.css'; import { env, AutoModel, ones } from '@xenova/transformers'; import Chart from 'chart.js/auto'; // Throw an error if WebGPU is not supported if (!navigator.gpu) { const err = 'WebGPU is not supported by this browser.'; alert(err) throw Error(err); } env.backends.onnx.wasm.wasmPaths = 'http...
transformers.js/examples/webgpu-embedding-benchmark/main.js/0
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module.exports = { root: true, env: { browser: true, es2020: true }, extends: [ 'eslint:recommended', 'plugin:react/recommended', 'plugin:react/jsx-runtime', 'plugin:react-hooks/recommended', ], ignorePatterns: ['dist', '.eslintrc.cjs'], parserOptions: { ecmaVersion: 'latest', sourceType: 'm...
transformers.js/examples/webgpu-vlm/.eslintrc.cjs/0
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export default function StopIcon(props) { return ( <svg {...props} xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" strokeWidth="2" strok...
transformers.js/examples/webgpu-vlm/src/components/icons/StopIcon.jsx/0
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import { useRef, useCallback, useEffect } from "react"; export function AudioVisualizer({ stream, ...props }) { const canvasRef = useRef(null); const visualize = useCallback((stream) => { const audioContext = new (window.AudioContext || window.webkitAudioContext)(); const source = audioContext...
transformers.js/examples/webgpu-whisper/src/components/AudioVisualizer.jsx/0
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import { useState, forwardRef, useRef, useImperativeHandle, useEffect, useCallback } from 'react'; const EXAMPLE_URL = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/whisper-timestamps-demo.mp4'; const MediaInput = forwardRef(({ onInputChange, onTimeUpdate, ...props }, ref) => { // UI s...
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def generate_tokenizer_json(tokenizer): vocab = tokenizer.get_vocab() normalizers = [] if tokenizer.normalize: # Lowercase the input string normalizers.append({ "type": "Lowercase", }) if tokenizer.language == 'ron': # Replace diacritics normalize...
transformers.js/scripts/extra/vits.py/0
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/** * @module generation/parameters */ /** * @typedef {Object} GenerationFunctionParameters * @property {import('../utils/tensor.js').Tensor} [inputs=null] (`Tensor` of varying shape depending on the modality, *optional*): * The sequence used as a prompt for the generation or as model inputs to the encoder. If `...
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import { ImageProcessor, post_process_object_detection, post_process_panoptic_segmentation, post_process_instance_segmentation, } from "../../base/image_processors_utils.js"; import { full } from '../../utils/tensor.js'; /** * @typedef {object} DetrFeatureExtractorResultProps * @property {import('...
transformers.js/src/models/detr/image_processing_detr.js/0
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import { ImageProcessor, } from "../../base/image_processors_utils.js"; export class VLMImageProcessor extends ImageProcessor { constructor(config) { super({ do_pad: true, pad_size: { width: config.image_size, height: config.image_size, ...
transformers.js/src/models/janus/image_processing_janus.js/0
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import { DonutImageProcessor } from "../donut/image_processing_donut.js"; // NOTE: extends DonutImageProcessor export class NougatImageProcessor extends DonutImageProcessor { }
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import { ImageProcessor, post_process_semantic_segmentation, } from "../../base/image_processors_utils.js"; export class SapiensImageProcessor extends ImageProcessor { /** @type {typeof post_process_semantic_segmentation} */ post_process_semantic_segmentation(...args) { return post_process_se...
transformers.js/src/models/sapiens/image_processing_sapiens.js/0
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import { AutoTokenizer } from "../../tokenizers.js"; import { AutoFeatureExtractor } from "../auto/feature_extraction_auto.js"; import { Processor } from "../../base/processing_utils.js"; export class Wav2Vec2Processor extends Processor { static tokenizer_class = AutoTokenizer static feature_extractor_class = ...
transformers.js/src/models/wav2vec2/processing_wav2vec2.js/0
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/** * The list of devices supported by Transformers.js */ export const DEVICE_TYPES = Object.freeze({ auto: 'auto', // Auto-detect based on device and environment gpu: 'gpu', // Auto-detect GPU cpu: 'cpu', // CPU wasm: 'wasm', // WebAssembly webgpu: 'webgpu', // WebGPU cuda: 'cuda', // CUDA ...
transformers.js/src/utils/devices.js/0
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import { DacFeatureExtractor, DacModel, DacEncoderModel, DacDecoderModel } from "../../../src/transformers.js"; import { MAX_MODEL_LOAD_TIME, MAX_TEST_EXECUTION_TIME, MAX_MODEL_DISPOSE_TIME, DEFAULT_MODEL_OPTIONS } from "../../init.js"; export default () => { describe("DacModel", () => { const model_id = "hf-in...
transformers.js/tests/models/dac/test_modeling_dac.js/0
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import { AutoImageProcessor, GLPNFeatureExtractor } from "../../../src/transformers.js"; import { load_cached_image } from "../../asset_cache.js"; import { MAX_PROCESSOR_LOAD_TIME, MAX_TEST_EXECUTION_TIME } from "../../init.js"; export default () => { // GLPNFeatureExtractor // - tests `size_divisor` and no size...
transformers.js/tests/models/glpn/test_image_processing_glpn.js/0
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import { AutoProcessor, JinaCLIPProcessor } from "../../../src/transformers.js"; import { load_cached_image } from "../../asset_cache.js"; import { MAX_PROCESSOR_LOAD_TIME, MAX_TEST_EXECUTION_TIME } from "../../init.js"; export default () => { describe("JinaCLIPProcessor", () => { const model_id = "jinaai/jina-...
transformers.js/tests/models/jina_clip/test_processor_jina_clip.js/0
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import { T5Tokenizer, MusicgenForConditionalGeneration, full } from "../../../src/transformers.js"; import { MAX_MODEL_LOAD_TIME, MAX_TEST_EXECUTION_TIME, MAX_MODEL_DISPOSE_TIME, DEFAULT_MODEL_OPTIONS } from "../../init.js"; export default () => { describe("MusicgenForConditionalGeneration", () => { const model...
transformers.js/tests/models/musicgen/test_modeling_musicgen.js/0
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import { Qwen2VLProcessor, Qwen2VLForConditionalGeneration, RawImage } from "../../../src/transformers.js"; import { MAX_MODEL_LOAD_TIME, MAX_TEST_EXECUTION_TIME, MAX_MODEL_DISPOSE_TIME, DEFAULT_MODEL_OPTIONS } from "../../init.js"; export default () => { const CONVERSATION = [ { role: "user", conte...
transformers.js/tests/models/qwen2_vl/test_modeling_qwen2_vl.js/0
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import { AutoFeatureExtractor, WeSpeakerFeatureExtractor } from "../../../src/transformers.js"; import { MAX_FEATURE_EXTRACTOR_LOAD_TIME, MAX_TEST_EXECUTION_TIME } from "../../init.js"; export default () => { // WeSpeakerFeatureExtractor describe("WeSpeakerFeatureExtractor", () => { const model_id = "onnx-com...
transformers.js/tests/models/wespeaker_resnet/test_feature_extraction_wespeaker_resnet.js/0
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import { pipeline, ImageSegmentationPipeline } from "../../src/transformers.js"; import { MAX_MODEL_LOAD_TIME, MAX_TEST_EXECUTION_TIME, MAX_MODEL_DISPOSE_TIME, DEFAULT_MODEL_OPTIONS } from "../init.js"; import { load_cached_image } from "../asset_cache.js"; const PIPELINE_ID = "image-segmentation"; export default ()...
transformers.js/tests/pipelines/test_pipelines_image_segmentation.js/0
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import { init } from "./init.js"; import { collect_and_execute_tests } from "./test_utils.js"; init(); await collect_and_execute_tests("Processors", "processor");
transformers.js/tests/processors.test.js/0
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# coding=utf-8 # Copyright 2022 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...
transformers/.circleci/create_circleci_config.py/0
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apiVersion: 1 datasources: - name: grafana-postgresql-datasource uid: be28nkzirtb0gd type: postgres url: $GRAFANA_POSTGRES_DATASOURCE_URL user: $GRAFANA_POSTGRES_DATASOURCE_USER secureJsonData: password: $GRAFANA_POSTGRES_DATASOURCE_PWD jsonData: database: metrics maxOpenConn...
transformers/benchmark/grafana_datasource.yaml/0
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FROM python:3.10-slim ENV PYTHONDONTWRITEBYTECODE=1 ARG REF=main USER root RUN apt-get update && apt-get install -y libsndfile1-dev espeak-ng time git libgl1 g++ tesseract-ocr git-lfs curl ENV UV_PYTHON=/usr/local/bin/python RUN pip --no-cache-dir install uv && uv pip install --no-cache-dir -U pip setuptools RUN uv pip...
transformers/docker/exotic-models.dockerfile/0
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#!/bin/bash source ~/.bashrc echo "running docker-entrypoint.sh" conda activate container echo $KUBE_GOOGLE_CLOUD_TPU_ENDPOINTS echo "printed TPU info" export XRT_TPU_CONFIG="tpu_worker;0;${KUBE_GOOGLE_CLOUD_TPU_ENDPOINTS:7}" exec "$@"#!/bin/bash
transformers/docker/transformers-pytorch-tpu/docker-entrypoint.sh/0
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# بناء نماذج مخصصة تم تصميم مكتبة 🤗 Transformers لتكون قابلة للتوسيع بسهولة. كل نموذج مُشفّر بالكامل في مجلد فرعي معين بالمستودع، دون أي تجريد، لذلك يمكنك بسهولة نسخ ملف النمذجة وتعديله وفقًا لاحتياجاتك. إذا كنت تُنشئ نموذجًا جديدًا تمامًا، فقد يكون من الأسهل البدء من الصفر. في هذا البرنامج التعليمي، سنُرِيك كيفية ك...
transformers/docs/source/ar/custom_models.md/0
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# تحميل المحوّلات باستخدام 🤗 PEFT [[open-in-colab]] تقنية "التدريب الدقيق ذو الكفاءة البارامتيرية" (PEFT)](https://huggingface.co/blog/peft) تقوم بتجميد معلمات النموذج المُدرب مسبقًا أثناء الضبط الدقيق وتضيف عدد صغير من المعلمات القابلة للتدريب (المحولات) فوقه. يتم تدريب المحوّلات لتعلم معلومات خاصة بالمهام. وقد ثبت...
transformers/docs/source/ar/peft.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 ...
transformers/docs/source/de/contributing.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...
transformers/docs/source/en/accelerate.md/0
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# Using Cursor as a client of transformers serve This example shows how to use `transformers serve` as a local LLM provider for [Cursor](https://cursor.com/), the popular IDE. In this particular case, requests to `transformers serve` will come from an external IP (Cursor's server IPs), which requires some additional s...
transformers/docs/source/en/cursor.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 ...
transformers/docs/source/en/installation.md/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 applicable law or agreed to...
transformers/docs/source/en/llm_tutorial_optimization.md/0
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<!--Copyright 2020 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...
transformers/docs/source/en/main_classes/processors.md/0
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<!--Copyright 2025 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...
transformers/docs/source/en/model_doc/aya_vision.md/0
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<!--Copyright 2020 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...
transformers/docs/source/en/model_doc/blenderbot-small.md/0
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<!--Copyright 2022 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/en/model_doc/clipseg.md/0
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<!--Copyright 2020 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...
transformers/docs/source/en/model_doc/ctrl.md/0
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<!--Copyright 2022 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/en/model_doc/donut.md/0
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<!--Copyright 2022 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/en/model_doc/esm.md/0
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<!--Copyright 2020 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...
transformers/docs/source/en/model_doc/fsmt.md/0
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<!--Copyright 2020 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...
transformers/docs/source/en/model_doc/gpt2.md/0
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<!--Copyright 2025 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...
transformers/docs/source/en/model_doc/lfm2_vl.md/0
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<!--Copyright 2020 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...
transformers/docs/source/en/model_doc/m2m_100.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...
transformers/docs/source/en/model_doc/mimi.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...
transformers/docs/source/en/model_doc/modernbert-decoder.md/0
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<!--Copyright 2020 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...
transformers/docs/source/en/model_doc/nllb.md/0
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<!--Copyright 2025 The NVIDIA NeMo Team and 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 requir...
transformers/docs/source/en/model_doc/parakeet.md/0
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<!--Copyright 2025 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...
transformers/docs/source/en/model_doc/rt_detr_v2.md/0
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<!--Copyright 2025 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...
transformers/docs/source/en/model_doc/smollm3.md/0
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<!--Copyright 2022 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/en/model_doc/switch_transformers.md/0
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<!--Copyright 2021 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/en/model_doc/visual_bert.md/0
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