text stringlengths 5 631k | id stringlengths 14 178 | metadata dict | __index_level_0__ int64 0 647 |
|---|---|---|---|
[
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [],
"seed": null,
"tokens": [
{
"id": 330,
"logprob": -0.09289551,
"special": false,
"text": " A"
},
{
... | text-generation-inference/integration-tests/models/__snapshots__/test_idefics2/test_flash_idefics2_next_load.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_idefics2/test_flash_idefics2_next_load.json",
"repo_id": "text-generation-inference",
"token_count": 4039
} | 313 |
[
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [
{
"id": 1276,
"logprob": null,
"text": "What"
},
{
"id": 310,
"logprob": -0.83984375,
"text": " is... | text-generation-inference/integration-tests/models/__snapshots__/test_mamba/test_mamba_load.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_mamba/test_mamba_load.json",
"repo_id": "text-generation-inference",
"token_count": 5458
} | 314 |
{
"details": {
"best_of_sequences": null,
"finish_reason": "eos_token",
"generated_tokens": 7,
"prefill": [
{
"id": 0,
"logprob": null,
"text": "<pad>"
}
],
"seed": null,
"tokens": [
{
"id": 3,
"logprob": -0.7001953,
"specia... | text-generation-inference/integration-tests/models/__snapshots__/test_t5_sharded/test_t5_sharded.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_t5_sharded/test_t5_sharded.json",
"repo_id": "text-generation-inference",
"token_count": 680
} | 315 |
{
"choices": [
{
"finish_reason": "stop",
"index": 0,
"logprobs": null,
"message": {
"content": "The image is a blank white space with no visible objects or features.",
"name": null,
"role": "assistant",
"tool_calls": null
},
"usage": null
}
... | text-generation-inference/integration-tests/models/__snapshots__/test_transformers_llama4/test_flash_llama4_image_base64_rgb_png.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_transformers_llama4/test_flash_llama4_image_base64_rgb_png.json",
"repo_id": "text-generation-inference",
"token_count": 283
} | 316 |
import pytest
import requests
@pytest.fixture(scope="module")
def llama_continue_final_message_handle(launcher):
with launcher("TinyLlama/TinyLlama-1.1B-Chat-v1.0") as handle:
yield handle
@pytest.fixture(scope="module")
async def llama_continue_final_message(llama_continue_final_message_handle):
aw... | text-generation-inference/integration-tests/models/test_continue_final_message.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_continue_final_message.py",
"repo_id": "text-generation-inference",
"token_count": 1102
} | 317 |
import pytest
@pytest.fixture(scope="module")
def flash_llama_marlin_handle(launcher):
with launcher(
"neuralmagic/llama-2-7b-chat-marlin", num_shard=2, quantize="marlin"
) as handle:
yield handle
@pytest.fixture(scope="module")
async def flash_llama_marlin(flash_llama_marlin_handle):
aw... | text-generation-inference/integration-tests/models/test_flash_llama_marlin.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_flash_llama_marlin.py",
"repo_id": "text-generation-inference",
"token_count": 748
} | 318 |
import pytest
@pytest.fixture(scope="module")
def flash_qwen2_5_vl_handle(launcher):
with launcher("Qwen/Qwen2.5-VL-3B-Instruct") as handle:
yield handle
@pytest.fixture(scope="module")
async def flash_qwen2_5(flash_qwen2_5_vl_handle):
await flash_qwen2_5_vl_handle.health(300)
return flash_qwen2... | text-generation-inference/integration-tests/models/test_flash_qwen2_5_vl.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_flash_qwen2_5_vl.py",
"repo_id": "text-generation-inference",
"token_count": 2258
} | 319 |
import pytest
import asyncio
@pytest.fixture(scope="module")
def mllama_handle(launcher):
with launcher(
"unsloth/Llama-3.2-11B-Vision-Instruct",
num_shard=2,
) as handle:
yield handle
@pytest.fixture(scope="module")
async def mllama(mllama_handle):
await mllama_handle.health(300... | text-generation-inference/integration-tests/models/test_mllama.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_mllama.py",
"repo_id": "text-generation-inference",
"token_count": 1584
} | 320 |
{
buildPythonPackage,
poetry-core,
aiohttp,
huggingface-hub,
pydantic,
}:
buildPythonPackage {
name = "text-generation";
src = ../clients/python;
pyproject = true;
build-system = [ poetry-core ];
dependencies = [
aiohttp
huggingface-hub
pydantic
];
}
| text-generation-inference/nix/client.nix/0 | {
"file_path": "text-generation-inference/nix/client.nix",
"repo_id": "text-generation-inference",
"token_count": 111
} | 321 |
use crate::infer::Infer;
use crate::{
default_parameters,
server::{generate_internal, ComputeType},
Deserialize, ErrorResponse, GenerateParameters, GenerateRequest, Serialize, ToSchema,
};
use axum::extract::{Extension, Path};
use axum::http::{HeaderMap, StatusCode};
use axum::response::IntoResponse;
use ax... | text-generation-inference/router/src/kserve.rs/0 | {
"file_path": "text-generation-inference/router/src/kserve.rs",
"repo_id": "text-generation-inference",
"token_count": 3533
} | 322 |
flash_att_v2_commit_cuda := v2.6.1
flash_att_v2_commit_rocm := 47bd46e0204a95762ae48712fd1a3978827c77fd
build-flash-attention-v2-cuda:
pip install -U packaging wheel
pip install flash-attn==$(flash_att_v2_commit_cuda)
install-flash-attention-v2-cuda: build-flash-attention-v2-cuda
echo "Flash v2 installed"
build-f... | text-generation-inference/server/Makefile-flash-att-v2/0 | {
"file_path": "text-generation-inference/server/Makefile-flash-att-v2",
"repo_id": "text-generation-inference",
"token_count": 397
} | 323 |
// Adapted from turboderp exllama: https://github.com/turboderp/exllama
#include <ATen/cuda/CUDAContext.h>
#include "q4_matrix.cuh"
#include <vector>
#include "../util.cuh"
#include "../matrix.cuh"
using namespace std;
const int UNSHUF_BLOCKSIZE_X = 64;
const int RECONS_THREADS_X = 64; // Block size and thread... | text-generation-inference/server/exllama_kernels/exllama_kernels/cuda_func/q4_matrix.cu/0 | {
"file_path": "text-generation-inference/server/exllama_kernels/exllama_kernels/cuda_func/q4_matrix.cu",
"repo_id": "text-generation-inference",
"token_count": 2592
} | 324 |
#include "q_matrix.cuh"
#include "matrix_view.cuh"
#include "util.cuh"
#include "quant/qdq_2.cuh"
#include "quant/qdq_3.cuh"
#include "quant/qdq_4.cuh"
#include "quant/qdq_5.cuh"
#include "quant/qdq_6.cuh"
#include "quant/qdq_8.cuh"
#define BLOCK_KN_SIZE 128
#define THREADS_X 32
#define THREADS_Y 32
// Shuffle quan... | text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/q_matrix.cu/0 | {
"file_path": "text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/q_matrix.cu",
"repo_id": "text-generation-inference",
"token_count": 10524
} | 325 |
import os
from typing import Optional
import torch
from text_generation_server.layers.attention.kv_cache import KVCache, KVScales
from text_generation_server.utils.import_utils import SYSTEM
from text_generation_server.layers.attention import Seqlen
from text_generation_server.utils.log import log_master
from text_gene... | text-generation-inference/server/text_generation_server/layers/attention/rocm.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/layers/attention/rocm.py",
"repo_id": "text-generation-inference",
"token_count": 5552
} | 326 |
import os
from dataclasses import dataclass
from typing import List, Optional, Union
import torch
from loguru import logger
from text_generation_server.utils.import_utils import SYSTEM
from text_generation_server.utils.log import log_once
from text_generation_server.utils.weights import (
Weight,
Weights,
... | text-generation-inference/server/text_generation_server/layers/gptq/__init__.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/layers/gptq/__init__.py",
"repo_id": "text-generation-inference",
"token_count": 9078
} | 327 |
import torch
from torch import nn
from typing import Tuple, Optional
from text_generation_server.utils.speculate import get_speculate
from text_generation_server.layers.linear import FastLinear
from text_generation_server.layers.tensor_parallel import (
TensorParallelHead,
TensorParallelColumnLinear,
)
class ... | text-generation-inference/server/text_generation_server/layers/medusa.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/layers/medusa.py",
"repo_id": "text-generation-inference",
"token_count": 2975
} | 328 |
# coding=utf-8
# Copyright 2024 Cohere team. All rights reserved.
#
# This code is based on EleutherAI's GPT-NeoX library and the GPT-NeoX
# and OPT implementations in this library. It has been modified from its
# original forms to accommodate minor architectural differences compared
# to GPT-NeoX and OPT used by the M... | text-generation-inference/server/text_generation_server/models/custom_modeling/flash_cohere_modeling.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/models/custom_modeling/flash_cohere_modeling.py",
"repo_id": "text-generation-inference",
"token_count": 8966
} | 329 |
import torch
import torch.distributed
from torch import nn
from transformers.activations import ACT2FN
from typing import Optional, List, Tuple
from text_generation_server.layers.attention import (
paged_attention,
attention,
Seqlen,
)
from text_generation_server.layers import (
TensorParallelMultiAda... | text-generation-inference/server/text_generation_server/models/custom_modeling/flash_qwen2_modeling.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/models/custom_modeling/flash_qwen2_modeling.py",
"repo_id": "text-generation-inference",
"token_count": 7370
} | 330 |
# 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/llava_next.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/models/custom_modeling/llava_next.py",
"repo_id": "text-generation-inference",
"token_count": 5362
} | 331 |
import torch
import torch.distributed
from transformers import AutoTokenizer, PreTrainedTokenizerBase
from typing import Optional, Union
from text_generation_server.models.custom_modeling.mamba_modeling import (
MambaConfig,
)
from loguru import logger
from text_generation_server.pb import generate_pb2
from text_ge... | text-generation-inference/server/text_generation_server/models/mamba.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/models/mamba.py",
"repo_id": "text-generation-inference",
"token_count": 15065
} | 332 |
import os
import torch
from torch.distributed import ProcessGroup
from datetime import timedelta
from loguru import logger
from text_generation_server.utils.import_utils import SYSTEM
# Tensor Parallelism settings
RANK = int(os.getenv("RANK", "0"))
WORLD_SIZE = int(os.getenv("WORLD_SIZE", "1"))
# CUDA memory fraction... | text-generation-inference/server/text_generation_server/utils/dist.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/utils/dist.py",
"repo_id": "text-generation-inference",
"token_count": 1916
} | 333 |
[package]
authors = ["Nicolas Patry <nicolas@huggingface.co>"]
edition = "2021"
name = "node"
version = "0.21.4-dev.0"
# See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html
[lib]
crate-type = ["cdylib"]
[dependencies]
napi = "2"
napi-derive = "2"
serde = { v... | tokenizers/bindings/node/Cargo.toml/0 | {
"file_path": "tokenizers/bindings/node/Cargo.toml",
"repo_id": "tokenizers",
"token_count": 221
} | 334 |
import { prependNormalizer, stripAccentsNormalizer, stripNormalizer } from '../../'
describe('stripNormalizer', () => {
it('instantiates with no parameters', () => {
const normalizer = stripNormalizer()
expect(normalizer.constructor.name).toEqual('Normalizer')
})
it('accepts `undefined` as first paramet... | tokenizers/bindings/node/lib/bindings/normalizers.test.ts/0 | {
"file_path": "tokenizers/bindings/node/lib/bindings/normalizers.test.ts",
"repo_id": "tokenizers",
"token_count": 468
} | 335 |
{
"name": "tokenizers-linux-arm-gnueabihf",
"version": "0.13.4-rc1",
"os": [
"linux"
],
"cpu": [
"arm"
],
"main": "tokenizers.linux-arm-gnueabihf.node",
"files": [
"tokenizers.linux-arm-gnueabihf.node"
],
"description": "Tokenizers platform specific bindings",
"keywords": [
"napi-r... | tokenizers/bindings/node/npm/linux-arm-gnueabihf/package.json/0 | {
"file_path": "tokenizers/bindings/node/npm/linux-arm-gnueabihf/package.json",
"repo_id": "tokenizers",
"token_count": 278
} | 336 |
tab_spaces = 2
| tokenizers/bindings/node/rustfmt.toml/0 | {
"file_path": "tokenizers/bindings/node/rustfmt.toml",
"repo_id": "tokenizers",
"token_count": 7
} | 337 |
export type TextInputSequence = string
export type PreTokenizedInputSequence = string[]
export type InputSequence = TextInputSequence | PreTokenizedInputSequence
export type TextEncodeInput = TextInputSequence | [TextInputSequence, TextInputSequence]
export type PreTokenizedEncodeInput = PreTokenizedInputSequence | [P... | tokenizers/bindings/node/types.ts/0 | {
"file_path": "tokenizers/bindings/node/types.ts",
"repo_id": "tokenizers",
"token_count": 114
} | 338 |
<jupyter_start><jupyter_code>!wget https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-uncased-vocab.txt -O /tmp/bert-base-uncased-vocab.txt
from tokenizers import BertWordPieceTokenizer
from tokenizers.tools import EncodingVisualizer
EncodingVisualizer.unk_token_regex.search("aaa[udsnk]aaa")
text = """Mathia... | tokenizers/bindings/python/examples/using_the_visualizer.ipynb/0 | {
"file_path": "tokenizers/bindings/python/examples/using_the_visualizer.ipynb",
"repo_id": "tokenizers",
"token_count": 1222
} | 339 |
# Generated content DO NOT EDIT
from .. import pre_tokenizers
PreTokenizer = pre_tokenizers.PreTokenizer
BertPreTokenizer = pre_tokenizers.BertPreTokenizer
ByteLevel = pre_tokenizers.ByteLevel
CharDelimiterSplit = pre_tokenizers.CharDelimiterSplit
Digits = pre_tokenizers.Digits
FixedLength = pre_tokenizers.FixedLength... | tokenizers/bindings/python/py_src/tokenizers/pre_tokenizers/__init__.py/0 | {
"file_path": "tokenizers/bindings/python/py_src/tokenizers/pre_tokenizers/__init__.py",
"repo_id": "tokenizers",
"token_count": 188
} | 340 |
use pyo3::exceptions;
use pyo3::prelude::*;
use pyo3::types::*;
use tk::tokenizer::{Offsets, PaddingDirection};
use tk::utils::truncation::TruncationDirection;
use tokenizers as tk;
use crate::error::{deprecation_warning, PyError};
/// The :class:`~tokenizers.Encoding` represents the output of a :class:`~tokenizers.T... | tokenizers/bindings/python/src/encoding.rs/0 | {
"file_path": "tokenizers/bindings/python/src/encoding.rs",
"repo_id": "tokenizers",
"token_count": 7328
} | 341 |
import argparse
import inspect
import os
from pathlib import Path
INDENT = " " * 4
GENERATED_COMMENT = "# Generated content DO NOT EDIT\n"
def do_indent(text: str, indent: str):
return text.replace("\n", f"\n{indent}")
def function(obj, indent, text_signature=None):
if text_signature is None:
text... | tokenizers/bindings/python/stub.py/0 | {
"file_path": "tokenizers/bindings/python/stub.py",
"repo_id": "tokenizers",
"token_count": 2392
} | 342 |
# Models
<tokenizerslangcontent>
<python>
## BPE
[[autodoc]] tokenizers.models.BPE
## Model
[[autodoc]] tokenizers.models.Model
## Unigram
[[autodoc]] tokenizers.models.Unigram
## WordLevel
[[autodoc]] tokenizers.models.WordLevel
## WordPiece
[[autodoc]] tokenizers.models.WordPiece
</python>
<rust>
The Rust A... | tokenizers/docs/source-doc-builder/api/models.mdx/0 | {
"file_path": "tokenizers/docs/source-doc-builder/api/models.mdx",
"repo_id": "tokenizers",
"token_count": 179
} | 343 |
Installation with npm
----------------------------------------------------------------------------------------------------
You can simply install 🤗 Tokenizers with npm using::
npm install tokenizers
| tokenizers/docs/source/installation/node.inc/0 | {
"file_path": "tokenizers/docs/source/installation/node.inc",
"repo_id": "tokenizers",
"token_count": 31
} | 344 |
#[macro_use]
extern crate criterion;
mod common;
use common::{iter_bench_encode, iter_bench_encode_batch, iter_bench_train};
use criterion::{Criterion, Throughput};
use std::hint::black_box;
use tokenizers::{
models::{bpe::BpeTrainerBuilder, TrainerWrapper},
EncodeInput, Tokenizer,
};
static BATCH_SIZE: usiz... | tokenizers/tokenizers/benches/llama3_benchmark.rs/0 | {
"file_path": "tokenizers/tokenizers/benches/llama3_benchmark.rs",
"repo_id": "tokenizers",
"token_count": 1034
} | 345 |
// A dependency graph that contains any wasm must all be imported
// asynchronously. This `bootstrap.js` file does the single async import, so
// that no one else needs to worry about it again.
import("./index.js")
.catch(e => console.error("Error importing `index.js`:", e));
| tokenizers/tokenizers/examples/unstable_wasm/www/bootstrap.js/0 | {
"file_path": "tokenizers/tokenizers/examples/unstable_wasm/www/bootstrap.js",
"repo_id": "tokenizers",
"token_count": 79
} | 346 |
//! [Byte Pair Encoding](https://www.aclweb.org/anthology/P16-1162/) model.
use std::{iter, mem};
mod model;
mod serialization;
pub mod trainer;
mod word;
type Pair = (u32, u32);
/// Errors that can be encountered while using or constructing a `BPE` model.
#[derive(thiserror::Error, Debug)]
pub enum Error {
/// ... | tokenizers/tokenizers/src/models/bpe/mod.rs/0 | {
"file_path": "tokenizers/tokenizers/src/models/bpe/mod.rs",
"repo_id": "tokenizers",
"token_count": 893
} | 347 |
use super::{super::OrderedVocabIter, WordPiece, WordPieceBuilder};
use ahash::{AHashMap, AHashSet};
use serde::{
de::{MapAccess, Visitor},
ser::SerializeStruct,
Deserialize, Deserializer, Serialize, Serializer,
};
impl Serialize for WordPiece {
fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::... | tokenizers/tokenizers/src/models/wordpiece/serialization.rs/0 | {
"file_path": "tokenizers/tokenizers/src/models/wordpiece/serialization.rs",
"repo_id": "tokenizers",
"token_count": 2534
} | 348 |
use crate::tokenizer::{Decoder, PreTokenizedString, PreTokenizer, Result, SplitDelimiterBehavior};
use serde::{de, Deserialize, Deserializer, Serialize};
/// Enum representing options for the metaspace prepending scheme.
#[derive(Debug, Clone, PartialEq, Serialize, Eq, Deserialize, Copy)]
#[serde(rename_all = "snake_c... | tokenizers/tokenizers/src/pre_tokenizers/metaspace.rs/0 | {
"file_path": "tokenizers/tokenizers/src/pre_tokenizers/metaspace.rs",
"repo_id": "tokenizers",
"token_count": 6687
} | 349 |
//! Represents a tokenization pipeline.
//!
//! A [`Tokenizer`](struct.Tokenizer.html) is composed of some of the following parts.
//! - [`Normalizer`](trait.Normalizer.html): Takes care of the text normalization (like unicode normalization).
//! - [`PreTokenizer`](trait.PreTokenizer.html): Takes care of the pre to... | tokenizers/tokenizers/src/tokenizer/mod.rs/0 | {
"file_path": "tokenizers/tokenizers/src/tokenizer/mod.rs",
"repo_id": "tokenizers",
"token_count": 22796
} | 350 |
use tokenizers::decoders::wordpiece::WordPiece as WordPieceDecoder;
use tokenizers::models::bpe::BPE;
use tokenizers::models::wordpiece::WordPiece;
use tokenizers::normalizers::bert::BertNormalizer;
use tokenizers::pre_tokenizers::bert::BertPreTokenizer;
use tokenizers::pre_tokenizers::byte_level::ByteLevel;
use tokeni... | tokenizers/tokenizers/tests/common/mod.rs/0 | {
"file_path": "tokenizers/tokenizers/tests/common/mod.rs",
"repo_id": "tokenizers",
"token_count": 811
} | 351 |
# Building a Vanilla JavaScript Application
In this tutorial, you’ll build a simple web application that detects objects in images using Transformers.js! To follow along, all you need is a code editor, a browser, and a simple server (e.g., VS Code Live Server).
Here's how it works: the user clicks “Upload image” and ... | transformers.js/docs/source/tutorials/vanilla-js.md/0 | {
"file_path": "transformers.js/docs/source/tutorials/vanilla-js.md",
"repo_id": "transformers.js",
"token_count": 3621
} | 352 |
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>Transformers.js - Code completion playground</title>
</head>
<body>
<div id="root"></div>
<script type="module" src="/src/main.jsx"></script>
</bod... | transformers.js/examples/code-completion/index.html/0 | {
"file_path": "transformers.js/examples/code-completion/index.html",
"repo_id": "transformers.js",
"token_count": 133
} | 353 |
{
"name": "cross-encoder",
"version": "0.0.0",
"lockfileVersion": 3,
"requires": true,
"packages": {
"": {
"name": "cross-encoder",
"version": "0.0.0",
"dependencies": {
"@xenova/transformers": "^2.15.0",
"react": "^18.2.0",
"react-dom": "^18.2.0"
},
"... | transformers.js/examples/cross-encoder/package-lock.json/0 | {
"file_path": "transformers.js/examples/cross-encoder/package-lock.json",
"repo_id": "transformers.js",
"token_count": 126976
} | 354 |
import path from 'path';
// Needed for deploying to GitHub pages
const BASE_PATH = process.env.BASE_PATH ?? '';
export default {
// config options
base: BASE_PATH,
root: path.join(__dirname, 'src'),
build: {
outDir: path.join(__dirname, 'dist')
},
publicDir: path.join(__dirname, 'publi... | transformers.js/examples/demo-site/vite.config.js/0 | {
"file_path": "transformers.js/examples/demo-site/vite.config.js",
"repo_id": "transformers.js",
"token_count": 126
} | 355 |
const { app, BrowserWindow, ipcMain } = require('electron');
const path = require('path');
const { session } = require('electron');
const { run } = require('./model.js');
// Handle creating/removing shortcuts on Windows when installing/uninstalling.
if (require('electron-squirrel-startup')) {
app.quit();
}
const... | transformers.js/examples/electron/src/index.js/0 | {
"file_path": "transformers.js/examples/electron/src/index.js",
"repo_id": "transformers.js",
"token_count": 796
} | 356 |
<!doctype html>
<html lang="en">
<head>
<meta charset="UTF-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>MusicGen Web | In-browser text-to-music w/ 🤗 Transformers.js!</title>
</head>
<body>
<div id="root"></div>
<script type="module" src="/src/main.jsx"... | transformers.js/examples/musicgen-web/index.html/0 | {
"file_path": "transformers.js/examples/musicgen-web/index.html",
"repo_id": "transformers.js",
"token_count": 145
} | 357 |
{
"name": "next",
"version": "0.1.0",
"private": true,
"scripts": {
"dev": "next dev",
"build": "next build",
"start": "next start",
"lint": "next lint"
},
"dependencies": {
"@huggingface/transformers": "^3.0.0-alpha.5",
"autoprefixer": "10.4.14",
"eslint": "8.45.0",
"eslint-... | transformers.js/examples/next-client/package.json/0 | {
"file_path": "transformers.js/examples/next-client/package.json",
"repo_id": "transformers.js",
"token_count": 280
} | 358 |
{
"name": "next",
"version": "0.1.0",
"lockfileVersion": 3,
"requires": true,
"packages": {
"": {
"name": "next",
"version": "0.1.0",
"dependencies": {
"@xenova/transformers": "^2.4.2",
"autoprefixer": "10.4.14",
"eslint": "8.45.0",
"eslint-config-next": "... | transformers.js/examples/next-server/package-lock.json/0 | {
"file_path": "transformers.js/examples/next-server/package-lock.json",
"repo_id": "transformers.js",
"token_count": 107116
} | 359 |
import http from 'http';
import querystring from 'querystring';
import url from 'url';
import { pipeline, env } from '@xenova/transformers';
class MyClassificationPipeline {
static task = 'text-classification';
static model = 'Xenova/distilbert-base-uncased-finetuned-sst-2-english';
static instance = null;
... | transformers.js/examples/node/esm/app.js/0 | {
"file_path": "transformers.js/examples/node/esm/app.js",
"repo_id": "transformers.js",
"token_count": 559
} | 360 |
import './style.css';
import { AutoModel, AutoProcessor, env, RawImage } from '@xenova/transformers';
// Since we will download the model from the Hugging Face Hub, we can skip the local model check
env.allowLocalModels = false;
// Proxy the WASM backend to prevent the UI from freezing
env.backends.onnx.wasm.proxy =... | transformers.js/examples/remove-background-client/main.js/0 | {
"file_path": "transformers.js/examples/remove-background-client/main.js",
"repo_id": "transformers.js",
"token_count": 1399
} | 361 |
{
"name": "semantic-audio-search",
"private": true,
"version": "0.0.0",
"type": "module",
"scripts": {
"dev": "vite",
"build": "vite build",
"preview": "vite preview"
},
"devDependencies": {
"vite": "^5.0.13"
},
"dependencies": {
"@xenova/transformers": "^2.10.1",
"deepscatter"... | transformers.js/examples/semantic-audio-search/package.json/0 | {
"file_path": "transformers.js/examples/semantic-audio-search/package.json",
"repo_id": "transformers.js",
"token_count": 168
} | 362 |
'use client'
export function SearchBar({ search }) {
return (<form
onSubmit={e => {
e.preventDefault();
const formData = new FormData(e.target);
const text = formData.get('text');
search(text);
}}
className='relative mb-2'
>
<div c... | transformers.js/examples/semantic-image-search-client/src/app/components/SearchBar.jsx/0 | {
"file_path": "transformers.js/examples/semantic-image-search-client/src/app/components/SearchBar.jsx",
"repo_id": "transformers.js",
"token_count": 734
} | 363 |
{
"name": "semantic-image-search",
"version": "0.1.0",
"private": true,
"scripts": {
"dev": "next dev",
"build": "next build",
"start": "next start",
"lint": "next lint"
},
"dependencies": {
"@supabase/supabase-js": "^2.31.0",
"@xenova/transformers": "^2.5.0",
"autoprefixer": "10... | transformers.js/examples/semantic-image-search/package.json/0 | {
"file_path": "transformers.js/examples/semantic-image-search/package.json",
"repo_id": "transformers.js",
"token_count": 319
} | 364 |
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/text-to-speech-client/.eslintrc.cjs/0 | {
"file_path": "transformers.js/examples/text-to-speech-client/.eslintrc.cjs",
"repo_id": "transformers.js",
"token_count": 211
} | 365 |
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8" />
<link rel="stylesheet" href="style.css" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>Transformers.js - Object Detection demo</title>
</head>
<body>
<main class="container">
<label class="... | transformers.js/examples/vanilla-js/index.html/0 | {
"file_path": "transformers.js/examples/vanilla-js/index.html",
"repo_id": "transformers.js",
"token_count": 316
} | 366 |
import {
AutoTokenizer,
CLIPTextModelWithProjection,
AutoProcessor,
CLIPVisionModelWithProjection,
RawImage,
dot,
softmax,
} from '@xenova/transformers';
import './style.css';
// Reference the elements that we will need
const status = document.getElementById('status');
const container = d... | transformers.js/examples/webgpu-clip/main.js/0 | {
"file_path": "transformers.js/examples/webgpu-clip/main.js",
"repo_id": "transformers.js",
"token_count": 2330
} | 367 |
import { useState } from "react";
import CrossIcon from "./icons/CrossIcon"
export default function ImagePreview({ src, onRemove, ...props }) {
const [hover, setHover] = useState(false);
return (
<div
{...props}
onMouseEnter={() => setHover(true)}
onMouseLeave={() =... | transformers.js/examples/webgpu-vlm/src/components/ImagePreview.jsx/0 | {
"file_path": "transformers.js/examples/webgpu-vlm/src/components/ImagePreview.jsx",
"repo_id": "transformers.js",
"token_count": 272
} | 368 |
<!doctype html>
<html lang="en">
<head>
<meta charset="UTF-8" />
<link rel="icon" type="image/png" href="/logo.png" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>Whisper WebGPU</title>
</head>
<body>
<div id="root"></div>
<script type="module" src="/src... | transformers.js/examples/webgpu-whisper/index.html/0 | {
"file_path": "transformers.js/examples/webgpu-whisper/index.html",
"repo_id": "transformers.js",
"token_count": 153
} | 369 |
# React + Vite
This template provides a minimal setup to get React working in Vite with HMR and some ESLint rules.
Currently, two official plugins are available:
- [@vitejs/plugin-react](https://github.com/vitejs/vite-plugin-react/blob/main/packages/plugin-react/README.md) uses [Babel](https://babeljs.io/) for Fast ... | transformers.js/examples/whisper-word-timestamps/README.md/0 | {
"file_path": "transformers.js/examples/whisper-word-timestamps/README.md",
"repo_id": "transformers.js",
"token_count": 152
} | 370 |
# Support exporting vision and text models separately:
# Adapted from https://github.com/huggingface/optimum/issues/1186#issuecomment-1637641760
from optimum.exporters.onnx.model_configs import CLIPTextOnnxConfig, ViTOnnxConfig
from typing import Dict
class CLIPVisionOnnxConfig(ViTOnnxConfig):
pass
class CLIPT... | transformers.js/scripts/extra/clip.py/0 | {
"file_path": "transformers.js/scripts/extra/clip.py",
"repo_id": "transformers.js",
"token_count": 439
} | 371 |
/**
* @file Processors are used to prepare inputs (e.g., text, image or audio) for a model.
*
* **Example:** Using a `WhisperProcessor` to prepare an audio input for a model.
* ```javascript
* import { AutoProcessor, read_audio } from '@huggingface/transformers';
*
* const processor = await AutoProcessor.from_... | transformers.js/src/base/processing_utils.js/0 | {
"file_path": "transformers.js/src/base/processing_utils.js",
"repo_id": "transformers.js",
"token_count": 2559
} | 372 |
import {
ImageProcessor,
} from "../../base/image_processors_utils.js";
export class ChineseCLIPFeatureExtractor extends ImageProcessor { }
| transformers.js/src/models/chinese_clip/image_processing_chinese_clip.js/0 | {
"file_path": "transformers.js/src/models/chinese_clip/image_processing_chinese_clip.js",
"repo_id": "transformers.js",
"token_count": 45
} | 373 |
import {
ImageProcessor,
} from "../../base/image_processors_utils.js";
export class GLPNFeatureExtractor extends ImageProcessor { }
| transformers.js/src/models/glpn/image_processing_glpn.js/0 | {
"file_path": "transformers.js/src/models/glpn/image_processing_glpn.js",
"repo_id": "transformers.js",
"token_count": 44
} | 374 |
import {
ImageProcessor,
} from "../../base/image_processors_utils.js";
export class MobileNetV2ImageProcessor extends ImageProcessor { }
export class MobileNetV2FeatureExtractor extends MobileNetV2ImageProcessor { }
| transformers.js/src/models/mobilenet_v2/image_processing_mobilenet_v2.js/0 | {
"file_path": "transformers.js/src/models/mobilenet_v2/image_processing_mobilenet_v2.js",
"repo_id": "transformers.js",
"token_count": 66
} | 375 |
import { Processor } from '../../base/processing_utils.js';
import { PyAnnoteFeatureExtractor } from './feature_extraction_pyannote.js';
export class PyAnnoteProcessor extends Processor {
static feature_extractor_class = PyAnnoteFeatureExtractor
/**
* Calls the feature_extractor function with the given a... | transformers.js/src/models/pyannote/processing_pyannote.js/0 | {
"file_path": "transformers.js/src/models/pyannote/processing_pyannote.js",
"repo_id": "transformers.js",
"token_count": 316
} | 376 |
import { AutoFeatureExtractor } from "../auto/feature_extraction_auto.js"
import { AutoTokenizer } from "../../tokenizers.js"
import { Processor } from "../../base/processing_utils.js"
/**
* Represents a UltravoxProcessor that extracts features from an audio input.
*/
export class UltravoxProcessor extends Processor... | transformers.js/src/models/ultravox/processing_ultravox.js/0 | {
"file_path": "transformers.js/src/models/ultravox/processing_ultravox.js",
"repo_id": "transformers.js",
"token_count": 852
} | 377 |
/**
* @file Tokenizers are used to prepare textual inputs for a model.
*
* **Example:** Create an `AutoTokenizer` and use it to tokenize a sentence.
* This will automatically detect the tokenizer type based on the tokenizer class defined in `tokenizer.json`.
* ```javascript
* import { AutoTokenizer } from '@hug... | transformers.js/src/tokenizers.js/0 | {
"file_path": "transformers.js/src/tokenizers.js",
"repo_id": "transformers.js",
"token_count": 71479
} | 378 |
import { AutoConfig, env } from "../src/transformers.js";
import { getFile } from "../src/utils/hub.js";
// Initialise the testing environment
env.allowLocalModels = false;
env.useFSCache = false;
const TEST_DATA = {
"Xenova/bert-base-uncased": {
model_type: "bert",
},
};
describe("Configs", () => {
for (c... | transformers.js/tests/configs.test.js/0 | {
"file_path": "transformers.js/tests/configs.test.js",
"repo_id": "transformers.js",
"token_count": 238
} | 379 |
import { AutoImageProcessor, CLIPFeatureExtractor } 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 () => {
// CLIPFeatureExtractor
// - tests center crop (do_center_cro... | transformers.js/tests/models/clip/test_image_processing_clip.js/0 | {
"file_path": "transformers.js/tests/models/clip/test_image_processing_clip.js",
"repo_id": "transformers.js",
"token_count": 464
} | 380 |
import { Florence2Processor, Florence2ForConditionalGeneration, RawImage, 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 () => {
const texts = ["Describe with a paragraph what is ... | transformers.js/tests/models/florence2/test_modeling_florence2.js/0 | {
"file_path": "transformers.js/tests/models/florence2/test_modeling_florence2.js",
"repo_id": "transformers.js",
"token_count": 1343
} | 381 |
import { PreTrainedTokenizer, HeliumForCausalLM } 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("HeliumForCausalLM", () => {
const model_id = "hf-internal-testing/t... | transformers.js/tests/models/helium/test_modeling_helium.js/0 | {
"file_path": "transformers.js/tests/models/helium/test_modeling_helium.js",
"repo_id": "transformers.js",
"token_count": 783
} | 382 |
import { AutoImageProcessor, MobileViTFeatureExtractor, MobileViTImageProcessor } 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 () => {
// MobileViTFeatureExtractor
des... | transformers.js/tests/models/mobilevit/test_image_processing_mobilevit.js/0 | {
"file_path": "transformers.js/tests/models/mobilevit/test_image_processing_mobilevit.js",
"repo_id": "transformers.js",
"token_count": 1322
} | 383 |
import { PatchTSTModel, PatchTSTForPrediction, Tensor } 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 dims = [64, 512, 7];
const prod = dims.reduce((a, b) => a * b, 1);
... | transformers.js/tests/models/patchtst/test_modeling_patchtst.js/0 | {
"file_path": "transformers.js/tests/models/patchtst/test_modeling_patchtst.js",
"repo_id": "transformers.js",
"token_count": 870
} | 384 |
import { VisionEncoderDecoderModel, 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("VisionEncoderDecoderModel", () => {
const model_id = "hf-internal-testing/... | transformers.js/tests/models/vision_encoder_decoder/test_modeling_vision_encoder_decoder.js/0 | {
"file_path": "transformers.js/tests/models/vision_encoder_decoder/test_modeling_vision_encoder_decoder.js",
"repo_id": "transformers.js",
"token_count": 752
} | 385 |
import { pipeline, DepthEstimationPipeline } 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 = "depth-estimation";
export default () => ... | transformers.js/tests/pipelines/test_pipelines_depth_estimation.js/0 | {
"file_path": "transformers.js/tests/pipelines/test_pipelines_depth_estimation.js",
"repo_id": "transformers.js",
"token_count": 917
} | 386 |
import { pipeline, TokenClassificationPipeline } from "../../src/transformers.js";
import { MAX_MODEL_LOAD_TIME, MAX_TEST_EXECUTION_TIME, MAX_MODEL_DISPOSE_TIME, DEFAULT_MODEL_OPTIONS } from "../init.js";
const PIPELINE_ID = "token-classification";
export default () => {
describe("Token Classification", () => {
... | transformers.js/tests/pipelines/test_pipelines_token_classification.js/0 | {
"file_path": "transformers.js/tests/pipelines/test_pipelines_token_classification.js",
"repo_id": "transformers.js",
"token_count": 2608
} | 387 |
import { Tensor, interpolate_4d, matmul, rfft, slice } from "../../src/transformers.js";
import { init } from "../init.js";
// Initialise the testing environment
init();
function expectToBeCloseToArray(actual, expected) {
expect(actual.length).toEqual(expected.length);
actual.forEach((x, i) => expect(x).toBeClose... | transformers.js/tests/utils/tensor_ops.test.js/0 | {
"file_path": "transformers.js/tests/utils/tensor_ops.test.js",
"repo_id": "transformers.js",
"token_count": 6379
} | 388 |
# 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 applicabl... | transformers/benchmark/benchmarks_entrypoint.py/0 | {
"file_path": "transformers/benchmark/benchmarks_entrypoint.py",
"repo_id": "transformers",
"token_count": 8546
} | 389 |
FROM python:3.9-slim
ENV PYTHONDONTWRITEBYTECODE=1
ARG REF=main
USER root
RUN apt-get update && apt-get install -y libsndfile1-dev espeak-ng time git cmake g++
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 install --no-cache-dir "git+... | transformers/docker/pipeline-tf.dockerfile/0 | {
"file_path": "transformers/docker/pipeline-tf.dockerfile",
"repo_id": "transformers",
"token_count": 227
} | 390 |
FROM google/cloud-sdk:slim
# Build args.
ARG GITHUB_REF=refs/heads/main
# TODO: This Dockerfile installs pytorch/xla 3.6 wheels. There are also 3.7
# wheels available; see below.
ENV PYTHON_VERSION=3.6
RUN apt-get update && apt-get install -y --no-install-recommends \
build-essential \
cmake \
... | transformers/docker/transformers-pytorch-tpu/Dockerfile/0 | {
"file_path": "transformers/docker/transformers-pytorch-tpu/Dockerfile",
"repo_id": "transformers",
"token_count": 1235
} | 391 |
# قوالب نماذج الدردشة
## مقدمة
تعد **الدردشة** أحد استخدامات نماذج اللغات الكبيرة (LLMs) شائعة الاستخدام بشكل متزايد. ففي سياق الدردشة، وبدلاً من متابعة سلسلة نصية واحدة (كما هو الحال مع نماذج اللغات القياسية)، يواصل النموذج بدلاً من ذلك محادثة تتكون من رسالة واحدة أو أكثر، تتضمن كل منها دورًا، مثل "المستخدم" أو "الم... | transformers/docs/source/ar/chat_templating.md/0 | {
"file_path": "transformers/docs/source/ar/chat_templating.md",
"repo_id": "transformers",
"token_count": 33667
} | 392 |
# المحولات النمطية
مكتبة `transformers` هي إطار عمل ذو فلسفة محدد؛ يتم تعريف فلسفتنا في [الدليل المفاهيمي](./philosophy).
جوهر هذه الفلسفة يتمثل في مبدأ [نموذج واحد، ملف واحد](https://huggingface.co/blog/transformers-design-philosophy)
في المكتبة. الجانب السلبي لهذا المكون هو تقييده لوراثة واستيراد مكونات الملفات.
ن... | transformers/docs/source/ar/modular_transformers.md/0 | {
"file_path": "transformers/docs/source/ar/modular_transformers.md",
"repo_id": "transformers",
"token_count": 6710
} | 393 |
<!--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 to... | transformers/docs/source/ar/tasks/masked_language_modeling.md/0 | {
"file_path": "transformers/docs/source/ar/tasks/masked_language_modeling.md",
"repo_id": "transformers",
"token_count": 9368
} | 394 |
- sections:
- local: index
title: 🤗 Transformers
- local: quicktour
title: Schnellstart
- local: installation
title: Installation
title: Erste Schritte
- sections:
- local: pipeline_tutorial
title: Pipelines für Inferenzen
- local: autoclass_tutorial
title: Laden von vortrainierten Inst... | transformers/docs/source/de/_toctree.yml/0 | {
"file_path": "transformers/docs/source/de/_toctree.yml",
"repo_id": "transformers",
"token_count": 430
} | 395 |
<!--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/de/testing.md/0 | {
"file_path": "transformers/docs/source/de/testing.md",
"repo_id": "transformers",
"token_count": 19213
} | 396 |
<!--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/chat_templating_multimodal.md/0 | {
"file_path": "transformers/docs/source/en/chat_templating_multimodal.md",
"repo_id": "transformers",
"token_count": 3715
} | 397 |
<!--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/glossary.md/0 | {
"file_path": "transformers/docs/source/en/glossary.md",
"repo_id": "transformers",
"token_count": 6761
} | 398 |
<!--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/model.md/0 | {
"file_path": "transformers/docs/source/en/main_classes/model.md",
"repo_id": "transformers",
"token_count": 508
} | 399 |
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