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": 510,
"logprob": -0.63183594,
"special": false,
"text": "The"
},
{
"id": 3159,
"logprob... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_neox_sharded/test_flash_neox.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_neox_sharded/test_flash_neox.json",
"repo_id": "text-generation-inference",
"token_count": 860
} | 303 |
{
"choices": [
{
"finish_reason": "stop",
"index": 0,
"logprobs": null,
"message": {
"content": "The image depicts an anthropomorphic rabbit character wearing an intricate space suit, which includes a helmet with a starry face pattern and multiple suitors. The rabbit's ears are sig... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_qwen2_5_vl/test_flash_qwen2_5_vl_simple.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_qwen2_5_vl/test_flash_qwen2_5_vl_simple.json",
"repo_id": "text-generation-inference",
"token_count": 388
} | 304 |
[
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [],
"seed": null,
"tokens": [
{
"id": 222,
"logprob": -1.9091797,
"special": false,
"text": "\n"
},
{
... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_starcoder2_lora/test_flash_starcoder2_load.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_starcoder2_lora/test_flash_starcoder2_load.json",
"repo_id": "text-generation-inference",
"token_count": 4084
} | 305 |
{
"details": {
"best_of_sequences": null,
"finish_reason": "eos_token",
"generated_tokens": 9,
"prefill": [],
"seed": null,
"tokens": [
{
"id": 2684,
"logprob": -0.24902344,
"special": false,
"text": " There"
},
{
"id": 374,
"lo... | text-generation-inference/integration-tests/models/__snapshots__/test_idefics3/test_flash_idefics3_next_simple_url.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_idefics3/test_flash_idefics3_next_simple_url.json",
"repo_id": "text-generation-inference",
"token_count": 796
} | 306 |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 17,
"prefill": [
{
"id": 1276,
"logprob": null,
"text": "What"
},
{
"id": 310,
"logprob": -1.5117188,
"text": " is"
},
{
"id": ... | text-generation-inference/integration-tests/models/__snapshots__/test_mpt/test_mpt.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_mpt/test_mpt.json",
"repo_id": "text-generation-inference",
"token_count": 1691
} | 307 |
{
"choices": [
{
"finish_reason": "stop",
"index": 0,
"logprobs": null,
"message": {
"content": "The image does not depict a dog; it shows a cow standing on a beach. Therefore, there is no breed of a dog to identify.",
"name": null,
"role": "assistant",
"too... | text-generation-inference/integration-tests/models/__snapshots__/test_transformers_llama4/test_flash_llama4_image_cow_dog.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_transformers_llama4/test_flash_llama4_image_cow_dog.json",
"repo_id": "text-generation-inference",
"token_count": 298
} | 308 |
import pytest
@pytest.fixture(scope="module")
def flash_deepseek_v2_handle(launcher):
with launcher("deepseek-ai/DeepSeek-V2-Lite", num_shard=2) as handle:
yield handle
@pytest.fixture(scope="module")
async def flash_deepseek_v2(flash_deepseek_v2_handle):
await flash_deepseek_v2_handle.health(300)
... | text-generation-inference/integration-tests/models/test_flash_deepseek_v2.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_flash_deepseek_v2.py",
"repo_id": "text-generation-inference",
"token_count": 710
} | 309 |
import pytest
@pytest.fixture(scope="module")
def flash_starcoder_handle(launcher):
with launcher("bigcode/starcoder", num_shard=2) as handle:
yield handle
@pytest.fixture(scope="module")
async def flash_starcoder(flash_starcoder_handle):
await flash_starcoder_handle.health(300)
return flash_sta... | text-generation-inference/integration-tests/models/test_flash_starcoder.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_flash_starcoder.py",
"repo_id": "text-generation-inference",
"token_count": 602
} | 310 |
import pytest
@pytest.fixture(scope="module")
def neox_handle(launcher):
with launcher(
"stabilityai/stablelm-tuned-alpha-3b", num_shard=1, use_flash_attention=False
) as handle:
yield handle
@pytest.fixture(scope="module")
async def neox(neox_handle):
await neox_handle.health(300)
r... | text-generation-inference/integration-tests/models/test_neox.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_neox.py",
"repo_id": "text-generation-inference",
"token_count": 515
} | 311 |
use std::fmt;
use std::process::Command;
pub(crate) struct Env {
cargo_target: &'static str,
cargo_version: &'static str,
git_sha: &'static str,
docker_label: &'static str,
nvidia_env: String,
xpu_env: String,
hpu_env: String,
}
impl Env {
pub fn new() -> Self {
let nvidia_env ... | text-generation-inference/launcher/src/env_runtime.rs/0 | {
"file_path": "text-generation-inference/launcher/src/env_runtime.rs",
"repo_id": "text-generation-inference",
"token_count": 1067
} | 312 |
{
lib,
mkShell,
black,
cmake,
isort,
ninja,
which,
cudaPackages,
openssl,
pkg-config,
poetry,
protobuf,
python3,
pyright,
redocly,
ruff,
rust-bin,
server,
# Enable dependencies for building CUDA packages. Useful for e.g.
# developing marlin/moe-kernels in-place.
withCuda ? fal... | text-generation-inference/nix/impure-shell.nix/0 | {
"file_path": "text-generation-inference/nix/impure-shell.nix",
"repo_id": "text-generation-inference",
"token_count": 1119
} | 313 |
use crate::infer::Infer;
use crate::server::{chat_completions, compat_generate, completions, ComputeType};
use crate::{
ChatCompletion, ChatCompletionChunk, ChatRequest, Chunk, CompatGenerateRequest,
CompletionFinal, CompletionRequest, ErrorResponse, GenerateResponse, Info, StreamResponse,
};
use axum::extract:... | text-generation-inference/router/src/sagemaker.rs/0 | {
"file_path": "text-generation-inference/router/src/sagemaker.rs",
"repo_id": "text-generation-inference",
"token_count": 1113
} | 314 |
commit_rocm := de990cd12537f78f74e40b5c8ee1a62d63d734dd
build-vllm-rocm:
if [ ! -d 'vllm' ]; then \
pip install -U ninja packaging --no-cache-dir && \
git clone https://github.com/mht-sharma/vllm.git vllm; \
fi
cd vllm && git fetch && git checkout $(commit_rocm) && \
PYTORCH_ROCM_ARCH="gfx90a;gfx942" python3 ... | text-generation-inference/server/Makefile-vllm/0 | {
"file_path": "text-generation-inference/server/Makefile-vllm",
"repo_id": "text-generation-inference",
"token_count": 201
} | 315 |
// Adapted from turboderp exllama: https://github.com/turboderp/exllama
#ifndef _hip_compat_cuh
#define _hip_compat_cuh
// Workaround for a bug in hipamd, backported from upstream, this is fixed in ROCm 5.6.
__device__ __forceinline__ __half __compat_hrcp(__half x) {
return __half_raw{
static_cast<_Float1... | text-generation-inference/server/exllama_kernels/exllama_kernels/hip_compat.cuh/0 | {
"file_path": "text-generation-inference/server/exllama_kernels/exllama_kernels/hip_compat.cuh",
"repo_id": "text-generation-inference",
"token_count": 1710
} | 316 |
#ifndef _qdq_3_cuh
#define _qdq_3_cuh
#include "qdq_util.cuh"
#include "../../config.h"
#if QMODE_3BIT == 1
// Permutation:
//
// v9997775 55333111 u8886664 44222000 (u, v lsb)
// vjjjhhhf ffdddbbb uiiiggge eecccaaa
// vtttrrrp ppnnnlll usssqqqo oommmkkk
__forceinline__ __device__ void shuffle_3bit_32
(
uin... | text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/quant/qdq_3.cuh/0 | {
"file_path": "text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/quant/qdq_3.cuh",
"repo_id": "text-generation-inference",
"token_count": 3335
} | 317 |
import pytest
import os
from text_generation_server.pb import generate_pb2
os.environ["PREFIX_CACHING"] = "1"
os.environ["ATTENTION"] = "flashinfer"
@pytest.fixture
def default_pb_parameters():
return generate_pb2.NextTokenChooserParameters(
temperature=1.0,
repetition_penalty=1.0,
top_k=... | text-generation-inference/server/tests/conftest.py/0 | {
"file_path": "text-generation-inference/server/tests/conftest.py",
"repo_id": "text-generation-inference",
"token_count": 235
} | 318 |
# Copied logic from https://github.com/mit-han-lab/llm-awq/blob/f084f40bd996f3cf3a0633c1ad7d9d476c318aaa/awq/quantize/qmodule.py
from typing import Optional
import torch
import torch.nn as nn
import awq_inference_engine # with CUDA kernels
# class ScaledActivation(nn.Module):
# def __init__(self, module, scales... | text-generation-inference/server/text_generation_server/layers/awq/quantize/cuda.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/layers/awq/quantize/cuda.py",
"repo_id": "text-generation-inference",
"token_count": 750
} | 319 |
# Adapted from turboderp exllama: https://github.com/turboderp/exllamav2
from dataclasses import dataclass
from typing import Optional
import torch
import torch.nn as nn
from loguru import logger
from text_generation_server.layers.exl2 import Exl2Weight
from text_generation_server.layers.gptq import GPTQWeight
from ... | text-generation-inference/server/text_generation_server/layers/gptq/exllamav2.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/layers/gptq/exllamav2.py",
"repo_id": "text-generation-inference",
"token_count": 3935
} | 320 |
from typing import Optional
import torch
import torch.nn as nn
from text_generation_server.utils.weights import Weights
from text_generation_server.layers.fp8 import (
Fp8Weight,
fp8_quantize,
quant_dtype,
normalize_e4m3fn_to_native_float8,
)
try:
from .unquantized import fused_moe
except Excepti... | text-generation-inference/server/text_generation_server/layers/moe/fp8.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/layers/moe/fp8.py",
"repo_id": "text-generation-inference",
"token_count": 2685
} | 321 |
"""A simple, flexible implementation of a GPT model.
Inspired by https://github.com/karpathy/minGPT/blob/master/mingpt/model.py
"""
import math
import warnings
from typing import List, Optional, Tuple, Union
import torch
import torch.nn as nn
import torch.nn.functional as F
from transformers import PreTrainedModel, P... | text-generation-inference/server/text_generation_server/models/custom_modeling/mpt_modeling.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/models/custom_modeling/mpt_modeling.py",
"repo_id": "text-generation-inference",
"token_count": 23706
} | 322 |
import inspect
import torch
from abc import ABC, abstractmethod
from typing import List, Tuple, Optional, TypeVar, Type, Dict
from collections import defaultdict
from transformers import PreTrainedTokenizerBase
from loguru import logger
from text_generation_server.models.globals import (
ATTENTION,
PREFIX_CAC... | text-generation-inference/server/text_generation_server/models/model.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/models/model.py",
"repo_id": "text-generation-inference",
"token_count": 2819
} | 323 |
import importlib
from loguru import logger
from kernels import load_kernel as hf_load_kernel
from text_generation_server.utils.log import log_once
def load_kernel(*, module: str, repo_id: str):
"""
Load a kernel. First try to load it as the given module (e.g. for
local development), falling back to a lo... | text-generation-inference/server/text_generation_server/utils/kernels.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/utils/kernels.py",
"repo_id": "text-generation-inference",
"token_count": 218
} | 324 |
# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!
cff-version: 1.2.0
title: HuggingFace's Tokenizers
message: >-
Fast State-of-the-Art Tokenizers optimized for Research
and Production.
type: software
authors:
- given-names: Anthony
family-names: Moi
... | tokenizers/CITATION.cff/0 | {
"file_path": "tokenizers/CITATION.cff",
"repo_id": "tokenizers",
"token_count": 293
} | 325 |
<p align="center">
<br>
<img src="https://huggingface.co/landing/assets/tokenizers/tokenizers-logo.png" width="600"/>
<br>
<p>
<p align="center">
<a href="https://badge.fury.io/js/tokenizers">
<img alt="Build" src="https://badge.fury.io/js/tokenizers.svg">
</a>
<a href="https://github.com/huggingface/to... | tokenizers/bindings/node/README.md/0 | {
"file_path": "tokenizers/bindings/node/README.md",
"repo_id": "tokenizers",
"token_count": 651
} | 326 |
/* eslint-disable @typescript-eslint/no-explicit-any */
/* eslint-disable @typescript-eslint/no-empty-function */
import { TruncationStrategy, BPE, Encoding, AddedToken, Tokenizer } from '../../'
// jest.mock('../../bindings/tokenizer');
// jest.mock('../../bindings/models', () => ({
// __esModule: true,
// Model... | tokenizers/bindings/node/lib/bindings/tokenizer.test.ts/0 | {
"file_path": "tokenizers/bindings/node/lib/bindings/tokenizer.test.ts",
"repo_id": "tokenizers",
"token_count": 5268
} | 327 |
# `tokenizers-linux-arm64-musl`
This is the **aarch64-unknown-linux-musl** binary for `tokenizers`
| tokenizers/bindings/node/npm/linux-arm64-musl/README.md/0 | {
"file_path": "tokenizers/bindings/node/npm/linux-arm64-musl/README.md",
"repo_id": "tokenizers",
"token_count": 37
} | 328 |
use crate::tokenizer::PaddingOptions;
use napi::bindgen_prelude::*;
use napi_derive::napi;
use tokenizers::utils::truncation::TruncationDirection;
use tokenizers::Encoding;
#[napi(js_name = "Encoding")]
#[derive(Clone, Default)]
pub struct JsEncoding {
pub(crate) encoding: Option<Encoding>,
}
impl From<Encoding> fo... | tokenizers/bindings/node/src/encoding.rs/0 | {
"file_path": "tokenizers/bindings/node/src/encoding.rs",
"repo_id": "tokenizers",
"token_count": 3778
} | 329 |
from .. import decoders
Decoder = decoders.Decoder
ByteLevel = decoders.ByteLevel
Replace = decoders.Replace
WordPiece = decoders.WordPiece
ByteFallback = decoders.ByteFallback
Fuse = decoders.Fuse
Strip = decoders.Strip
Metaspace = decoders.Metaspace
BPEDecoder = decoders.BPEDecoder
CTC = decoders.CTC
Sequence = dec... | tokenizers/bindings/python/py_src/tokenizers/decoders/__init__.py/0 | {
"file_path": "tokenizers/bindings/python/py_src/tokenizers/decoders/__init__.py",
"repo_id": "tokenizers",
"token_count": 140
} | 330 |
# Generated content DO NOT EDIT
class PostProcessor:
"""
Base class for all post-processors
This class is not supposed to be instantiated directly. Instead, any implementation of
a PostProcessor will return an instance of this class when instantiated.
"""
def num_special_tokens_to_add(self, is_... | tokenizers/bindings/python/py_src/tokenizers/processors/__init__.pyi/0 | {
"file_path": "tokenizers/bindings/python/py_src/tokenizers/processors/__init__.pyi",
"repo_id": "tokenizers",
"token_count": 4779
} | 331 |
use std::collections::HashMap;
use std::path::{Path, PathBuf};
use std::sync::{Arc, RwLock};
use crate::token::PyToken;
use crate::trainers::PyTrainer;
use ahash::AHashMap;
use pyo3::exceptions;
use pyo3::prelude::*;
use pyo3::types::*;
use serde::{Deserialize, Serialize};
use tk::models::bpe::{BpeBuilder, Merges, BPE... | tokenizers/bindings/python/src/models.rs/0 | {
"file_path": "tokenizers/bindings/python/src/models.rs",
"repo_id": "tokenizers",
"token_count": 16127
} | 332 |
from tokenizers import ByteLevelBPETokenizer
from ..utils import data_dir, multiprocessing_with_parallelism, roberta_files
class TestByteLevelBPE:
def test_basic_encode(self, roberta_files):
tokenizer = ByteLevelBPETokenizer.from_file(roberta_files["vocab"], roberta_files["merges"])
output = toke... | tokenizers/bindings/python/tests/implementations/test_byte_level_bpe.py/0 | {
"file_path": "tokenizers/bindings/python/tests/implementations/test_byte_level_bpe.py",
"repo_id": "tokenizers",
"token_count": 1653
} | 333 |
# Pre-tokenizers
<tokenizerslangcontent>
<python>
## BertPreTokenizer
[[autodoc]] tokenizers.pre_tokenizers.BertPreTokenizer
## ByteLevel
[[autodoc]] tokenizers.pre_tokenizers.ByteLevel
## CharDelimiterSplit
[[autodoc]] tokenizers.pre_tokenizers.CharDelimiterSplit
## Digits
[[autodoc]] tokenizers.pre_tokenizers... | tokenizers/docs/source-doc-builder/api/pre-tokenizers.mdx/0 | {
"file_path": "tokenizers/docs/source-doc-builder/api/pre-tokenizers.mdx",
"repo_id": "tokenizers",
"token_count": 371
} | 334 |
The tokenization pipeline
====================================================================================================
When calling :entity:`Tokenizer.encode` or :entity:`Tokenizer.encode_batch`, the input text(s) go
through the following pipeline:
- :ref:`normalization`
- :ref:`pre-tokenization`
- :ref:`mode... | tokenizers/docs/source/pipeline.rst/0 | {
"file_path": "tokenizers/docs/source/pipeline.rst",
"repo_id": "tokenizers",
"token_count": 6322
} | 335 |
use tokenizers::models::wordpiece::WordPiece;
use tokenizers::{AddedToken, Tokenizer};
fn main() {
let start = std::time::Instant::now();
let mut tokenizer = Tokenizer::new(WordPiece::default());
// Mix special and not special
// You can make sure ids are in order, and special status is correct.
l... | tokenizers/tokenizers/examples/serialization.rs/0 | {
"file_path": "tokenizers/tokenizers/examples/serialization.rs",
"repo_id": "tokenizers",
"token_count": 299
} | 336 |
{
"name": "create-wasm-app",
"version": "0.1.0",
"lockfileVersion": 2,
"requires": true,
"packages": {
"": {
"name": "create-wasm-app",
"version": "0.1.0",
"license": "(MIT OR Apache-2.0)",
"dependencies": {
"unstable_wasm": "fi... | tokenizers/tokenizers/examples/unstable_wasm/www/package-lock.json/0 | {
"file_path": "tokenizers/tokenizers/examples/unstable_wasm/www/package-lock.json",
"repo_id": "tokenizers",
"token_count": 193670
} | 337 |
#![allow(clippy::map_entry)]
use super::{Pair, WithFirstLastIterator, Word, BPE};
use crate::parallelism::*;
use crate::tokenizer::{AddedToken, Result, Trainer};
use crate::utils::progress::{ProgressBar, ProgressStyle};
use ahash::{AHashMap, AHashSet};
use compact_str::CompactString;
use dary_heap::OctonaryHeap;
use s... | tokenizers/tokenizers/src/models/bpe/trainer.rs/0 | {
"file_path": "tokenizers/tokenizers/src/models/bpe/trainer.rs",
"repo_id": "tokenizers",
"token_count": 14629
} | 338 |
use crate::processors::byte_level::bytes_char;
use crate::tokenizer::{NormalizedString, Normalizer, Result};
use crate::utils::macro_rules_attribute;
use ahash::{AHashMap, AHashSet};
use std::sync::LazyLock;
#[derive(Clone, Debug)]
#[macro_rules_attribute(impl_serde_type!)]
pub struct ByteLevel;
static BYTES_CHAR: La... | tokenizers/tokenizers/src/normalizers/byte_level.rs/0 | {
"file_path": "tokenizers/tokenizers/src/normalizers/byte_level.rs",
"repo_id": "tokenizers",
"token_count": 3351
} | 339 |
use crate::pre_tokenizers::PreTokenizerWrapper;
use crate::tokenizer::{PreTokenizedString, PreTokenizer, Result};
use crate::utils::macro_rules_attribute;
use serde::{Deserialize, Serialize};
#[derive(Clone, Debug, PartialEq)]
#[macro_rules_attribute(impl_serde_type!)]
pub struct Sequence {
pretokenizers: Vec<PreT... | tokenizers/tokenizers/src/pre_tokenizers/sequence.rs/0 | {
"file_path": "tokenizers/tokenizers/src/pre_tokenizers/sequence.rs",
"repo_id": "tokenizers",
"token_count": 1124
} | 340 |
use crate::{
normalizer::Range, Encoding, NormalizedString, OffsetReferential, Offsets, Result, Token,
};
use std::collections::HashMap;
/// Various possible types of offsets
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub enum OffsetType {
Byte,
Char,
None,
}
/// Wrapper for a subpart of a `Normaliz... | tokenizers/tokenizers/src/tokenizer/pre_tokenizer.rs/0 | {
"file_path": "tokenizers/tokenizers/src/tokenizer/pre_tokenizer.rs",
"repo_id": "tokenizers",
"token_count": 5310
} | 341 |
mod common;
use common::*;
use tokenizers::tokenizer::AddedToken;
macro_rules! check_offsets {
($input: expr, $output:expr, $offset:expr, $result:expr) => {
let offsets = $output.get_offsets()[$offset];
assert_eq!(&$input[offsets.0..offsets.1], $result);
};
}
#[test]
fn byte_level_basic() {
... | tokenizers/tokenizers/tests/offsets.rs/0 | {
"file_path": "tokenizers/tokenizers/tests/offsets.rs",
"repo_id": "tokenizers",
"token_count": 2497
} | 342 |
{
"overrides": [
{
"files": ["tests/**/*.js"],
"options": {
"printWidth": 10000000
}
}
]
}
| transformers.js/.prettierrc/0 | {
"file_path": "transformers.js/.prettierrc",
"repo_id": "transformers.js",
"token_count": 108
} | 343 |
# Use custom models
<include>
{
"path": "../snippets/4_custom-usage.snippet"
}
</include> | transformers.js/docs/source/custom_usage.md/0 | {
"file_path": "transformers.js/docs/source/custom_usage.md",
"repo_id": "transformers.js",
"token_count": 40
} | 344 |
#root {
height: 100vh;
width: 100vw;
padding: 1rem;
}
| transformers.js/examples/cross-encoder/src/App.css/0 | {
"file_path": "transformers.js/examples/cross-encoder/src/App.css",
"repo_id": "transformers.js",
"token_count": 29
} | 345 |
import './style.css';
import * as THREE from 'three';
import { OrbitControls } from 'three/addons/controls/OrbitControls.js';
import { pipeline, 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;
... | transformers.js/examples/depth-anything-client/main.js/0 | {
"file_path": "transformers.js/examples/depth-anything-client/main.js",
"repo_id": "transformers.js",
"token_count": 1584
} | 346 |
#root {
max-width: 960px;
height: 100vh;
margin: 0 auto;
text-align: center;
display: flex;
justify-content: center;
align-items: center;
}
| transformers.js/examples/musicgen-web/src/App.css/0 | {
"file_path": "transformers.js/examples/musicgen-web/src/App.css",
"repo_id": "transformers.js",
"token_count": 60
} | 347 |
* {
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,
h4 {
text-align: center;
}
h4 {... | transformers.js/examples/remove-background-client/style.css/0 | {
"file_path": "transformers.js/examples/remove-background-client/style.css",
"repo_id": "transformers.js",
"token_count": 422
} | 348 |
import { env, AutoTokenizer, ClapTextModelWithProjection } from '@xenova/transformers';
import { getCachedFile } from './utils';
// Skip local model check
env.allowLocalModels = false;
class ApplicationSingleton {
static model_id = 'Xenova/larger_clap_music_and_speech';
static BASE_URL = 'https://huggingface... | transformers.js/examples/semantic-audio-search/worker.js/0 | {
"file_path": "transformers.js/examples/semantic-audio-search/worker.js",
"repo_id": "transformers.js",
"token_count": 1294
} | 349 |
import './globals.css'
import { Inter } from 'next/font/google'
const inter = Inter({ subsets: ['latin'] })
export const metadata = {
title: 'In-browser Semantic Image Search',
description: 'Search for images using text (built w/ Transformers.js)',
}
export default function RootLayout({ children }) {
return (
... | transformers.js/examples/semantic-image-search-client/src/app/layout.js/0 | {
"file_path": "transformers.js/examples/semantic-image-search-client/src/app/layout.js",
"repo_id": "transformers.js",
"token_count": 139
} | 350 |
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>Transformers.js - Text-to-speech demo</title>
</head>
<body>
<div id="root"></div>
<script type="module" src="/src/main.jsx"></script>
</body>
</ht... | transformers.js/examples/text-to-speech-client/index.html/0 | {
"file_path": "transformers.js/examples/text-to-speech-client/index.html",
"repo_id": "transformers.js",
"token_count": 136
} | 351 |
import { marked } from 'marked';
import DOMPurify from 'dompurify';
import BotIcon from './icons/BotIcon';
import UserIcon from './icons/UserIcon';
import './Chat.css';
export default function Chat({ messages }) {
const empty = messages.length === 0;
return (<div className={`flex-1 p-6 max-w-[960px] w-full ... | transformers.js/examples/webgpu-chat/src/components/Chat.jsx/0 | {
"file_path": "transformers.js/examples/webgpu-chat/src/components/Chat.jsx",
"repo_id": "transformers.js",
"token_count": 1362
} | 352 |
import { defineConfig } from 'vite';
export default defineConfig({
build: {
target: 'esnext'
}
});
| transformers.js/examples/webgpu-clip/vite.config.js/0 | {
"file_path": "transformers.js/examples/webgpu-clip/vite.config.js",
"repo_id": "transformers.js",
"token_count": 37
} | 353 |
{
"name": "webgpu-video-depth-estimation",
"private": true,
"version": "0.0.0",
"type": "module",
"scripts": {
"dev": "vite",
"build": "vite build",
"preview": "vite preview"
},
"devDependencies": {
"vite": "^5.2.0"
},
"dependencies": {
"@xenova/transformers": "github:xenova/transf... | transformers.js/examples/webgpu-video-depth-estimation/package.json/0 | {
"file_path": "transformers.js/examples/webgpu-video-depth-estimation/package.json",
"repo_id": "transformers.js",
"token_count": 157
} | 354 |
export default function BotIcon(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"
stroke... | transformers.js/examples/webgpu-vlm/src/components/icons/BotIcon.jsx/0 | {
"file_path": "transformers.js/examples/webgpu-vlm/src/components/icons/BotIcon.jsx",
"repo_id": "transformers.js",
"token_count": 392
} | 355 |
import random
from typing import Optional, Tuple
from optimum.exporters.onnx.config import TextDecoderOnnxConfig
from optimum.utils import NormalizedTextConfig, DummyInputGenerator, DEFAULT_DUMMY_SHAPES, DummyTextInputGenerator, NormalizedConfig
class OpenElmDummyPastKeyValuesGenerator(DummyInputGenerator):
SUPP... | transformers.js/scripts/extra/openelm.py/0 | {
"file_path": "transformers.js/scripts/extra/openelm.py",
"repo_id": "transformers.js",
"token_count": 1129
} | 356 |
/**
* @module generation/configuration_utils
*/
import { pick } from "../utils/core.js";
/**
* Class that holds a configuration for a generation task.
*/
export class GenerationConfig {
// Parameters that control the length of the output
/**
* The maximum length the generated tokens can have.
*... | transformers.js/src/generation/configuration_utils.js/0 | {
"file_path": "transformers.js/src/generation/configuration_utils.js",
"repo_id": "transformers.js",
"token_count": 4706
} | 357 |
import {
ImageProcessor,
} from "../../base/image_processors_utils.js";
export class ConvNextImageProcessor extends ImageProcessor {
constructor(config) {
super(config);
/**
* Percentage of the image to crop. Only has an effect if this.size < 384.
*/
// @ts-expect-er... | transformers.js/src/models/convnext/image_processing_convnext.js/0 | {
"file_path": "transformers.js/src/models/convnext/image_processing_convnext.js",
"repo_id": "transformers.js",
"token_count": 683
} | 358 |
import {
ImageProcessor,
} from "../../base/image_processors_utils.js";
import { cat, full, interpolate_4d, slice, stack } from "../../utils/tensor.js";
export class Idefics3ImageProcessor extends ImageProcessor {
constructor(config) {
super(config);
this.do_image_splitting = config.do_image... | transformers.js/src/models/idefics3/image_processing_idefics3.js/0 | {
"file_path": "transformers.js/src/models/idefics3/image_processing_idefics3.js",
"repo_id": "transformers.js",
"token_count": 4603
} | 359 |
import {
ImageProcessor,
} from "../../base/image_processors_utils.js";
export class MobileViTImageProcessor extends ImageProcessor { }
export class MobileViTFeatureExtractor extends MobileViTImageProcessor { }
| transformers.js/src/models/mobilevit/image_processing_mobilevit.js/0 | {
"file_path": "transformers.js/src/models/mobilevit/image_processing_mobilevit.js",
"repo_id": "transformers.js",
"token_count": 64
} | 360 |
import {
ImageProcessor,
post_process_object_detection,
} from "../../base/image_processors_utils.js";
export class RTDetrImageProcessor extends ImageProcessor {
/** @type {typeof post_process_object_detection} */
post_process_object_detection(...args) {
return post_process_object_detection(.... | transformers.js/src/models/rt_detr/image_processing_rt_detr.js/0 | {
"file_path": "transformers.js/src/models/rt_detr/image_processing_rt_detr.js",
"repo_id": "transformers.js",
"token_count": 122
} | 361 |
import {
ImageProcessor,
} from "../../base/image_processors_utils.js";
export class VitPoseImageProcessor extends ImageProcessor {
/**
* Transform the heatmaps into keypoint predictions and transform them back to the image.
* NOTE: This is a naive implementation and does not include advanced post-p... | transformers.js/src/models/vitpose/image_processing_vitpose.js/0 | {
"file_path": "transformers.js/src/models/vitpose/image_processing_vitpose.js",
"repo_id": "transformers.js",
"token_count": 1796
} | 362 |
export const GITHUB_ISSUE_URL = 'https://github.com/huggingface/transformers.js/issues/new/choose';
export const CONFIG_NAME = "config.json"
export const FEATURE_EXTRACTOR_NAME = "preprocessor_config.json"
export const IMAGE_PROCESSOR_NAME = FEATURE_EXTRACTOR_NAME
export const PROCESSOR_NAME = "processor_config.json"... | transformers.js/src/utils/constants.js/0 | {
"file_path": "transformers.js/src/utils/constants.js",
"repo_id": "transformers.js",
"token_count": 149
} | 363 |
// Helper functions used when initialising the testing environment.
// Import Node typing utilities
import * as types from "node:util/types";
// Import onnxruntime-node's default backend
import { onnxruntimeBackend } from "onnxruntime-node/dist/backend";
import * as ONNX_COMMON from "onnxruntime-common";
/**
* A wo... | transformers.js/tests/init.js/0 | {
"file_path": "transformers.js/tests/init.js",
"repo_id": "transformers.js",
"token_count": 2091
} | 364 |
import { CodeGenTokenizer, CodeGenForCausalLM } 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("CodeGenForCausalLM", () => {
const model_id = "hf-internal-testing/ti... | transformers.js/tests/models/codegen/test_modeling_codegen.js/0 | {
"file_path": "transformers.js/tests/models/codegen/test_modeling_codegen.js",
"repo_id": "transformers.js",
"token_count": 768
} | 365 |
import { PreTrainedTokenizer, JAISLMHeadModel } 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("JAISLMHeadModel", () => {
const model_id = "onnx-community/tiny-rando... | transformers.js/tests/models/jais/test_modeling_jais.js/0 | {
"file_path": "transformers.js/tests/models/jais/test_modeling_jais.js",
"repo_id": "transformers.js",
"token_count": 798
} | 366 |
import { Wav2Vec2Processor, MoonshineForConditionalGeneration, full, ones } 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("MoonshineForConditionalGeneration", () => {
... | transformers.js/tests/models/moonshine/test_modeling_moonshine.js/0 | {
"file_path": "transformers.js/tests/models/moonshine/test_modeling_moonshine.js",
"repo_id": "transformers.js",
"token_count": 724
} | 367 |
import { AutoProcessor, AutoModelForAudioFrameClassification } from "../../../src/transformers.js";
import { MAX_TEST_EXECUTION_TIME, DEFAULT_MODEL_OPTIONS } from "../../init.js";
import { compare } from "../../test_utils.js";
export default () => {
const models_to_test = ["onnx-community/pyannote-segmentation-3.0"... | transformers.js/tests/models/pyannote/test_modeling_pyannote.js/0 | {
"file_path": "transformers.js/tests/models/pyannote/test_modeling_pyannote.js",
"repo_id": "transformers.js",
"token_count": 1018
} | 368 |
import { AutoImageProcessor, rand, Tensor, VitPoseImageProcessor } 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("VitPoseImageProcessor", () => {
con... | transformers.js/tests/models/vitpose/test_image_processing_vitpose.js/0 | {
"file_path": "transformers.js/tests/models/vitpose/test_image_processing_vitpose.js",
"repo_id": "transformers.js",
"token_count": 725
} | 369 |
import { pipeline, FillMaskPipeline } 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 = "fill-mask";
export default () => {
describe("Fill Mask", () => {
describe("Standard", () => {
... | transformers.js/tests/pipelines/test_pipelines_fill_mask.js/0 | {
"file_path": "transformers.js/tests/pipelines/test_pipelines_fill_mask.js",
"repo_id": "transformers.js",
"token_count": 3763
} | 370 |
import { pipeline, ZeroShotAudioClassificationPipeline } 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_audio } from "../asset_cache.js";
const PIPELINE_ID = "zero-shot-audio-classificatio... | transformers.js/tests/pipelines/test_pipelines_zero_shot_audio_classification.js/0 | {
"file_path": "transformers.js/tests/pipelines/test_pipelines_zero_shot_audio_classification.js",
"repo_id": "transformers.js",
"token_count": 827
} | 371 |
import { fileURLToPath } from "node:url";
import path from "node:path";
import fs from "node:fs";
import webpack from "webpack";
import TerserPlugin from "terser-webpack-plugin";
const __dirname = path.dirname(fileURLToPath(import.meta.url));
/**
* Plugin to strip the "node:" prefix from module requests.
*
* This... | transformers.js/webpack.config.js/0 | {
"file_path": "transformers.js/webpack.config.js",
"repo_id": "transformers.js",
"token_count": 2352
} | 372 |
# Contributor Covenant Code of Conduct
## Our Pledge
We as members, contributors, and leaders pledge to make participation in our
community a harassment-free experience for everyone, regardless of age, body
size, visible or invisible disability, ethnicity, sex characteristics, gender
identity and expression, level o... | transformers/CODE_OF_CONDUCT.md/0 | {
"file_path": "transformers/CODE_OF_CONDUCT.md",
"repo_id": "transformers",
"token_count": 1206
} | 373 |
{
"annotations": {
"list": [
{
"builtIn": 1,
"datasource": {
"type": "grafana",
"uid": "-- Grafana --"
},
"enable": true,
"hide": true,
"iconColor": "rgba(0, 211, 255, 1)",
"name": "Annotations & Alerts",
"type": "dashboard"... | transformers/benchmark/grafana_dashboard.json/0 | {
"file_path": "transformers/benchmark/grafana_dashboard.json",
"repo_id": "transformers",
"token_count": 42595
} | 374 |
#!/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 | {
"file_path": "transformers/docker/transformers-pytorch-tpu/docker-entrypoint.sh",
"repo_id": "transformers",
"token_count": 112
} | 375 |
# إنشاء بنية مخصصة
تحدد فئة [`AutoClass`](model_doc/auto) تلقائيًا بنية النموذج وتقوم بتنزيل تكوين وأوزان مسبقين للنموذج. بشكل عام، نوصي باستخدام `AutoClass` لإنتاج كود غير مرتبط بنسخة معينة. ولكن يمكن للمستخدمين الذين يريدون مزيدًا من التحكم في معلمات النموذج المحددة إنشاء نموذج مخصص من 🤗 Transformers من مجرد بضع ف... | transformers/docs/source/ar/create_a_model.md/0 | {
"file_path": "transformers/docs/source/ar/create_a_model.md",
"repo_id": "transformers",
"token_count": 12069
} | 376 |
<!--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/add_new_pipeline.md/0 | {
"file_path": "transformers/docs/source/de/add_new_pipeline.md",
"repo_id": "transformers",
"token_count": 4535
} | 377 |
# Optimizing inference
perf_infer_gpu_many: perf_infer_gpu_one
transformers_agents: agents
quantization: quantization/overview
| transformers/docs/source/en/_redirects.yml/0 | {
"file_path": "transformers/docs/source/en/_redirects.yml",
"repo_id": "transformers",
"token_count": 41
} | 378 |
<!---
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 ... | transformers/docs/source/en/contributing.md/0 | {
"file_path": "transformers/docs/source/en/contributing.md",
"repo_id": "transformers",
"token_count": 5163
} | 379 |
<!--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/image_processors.md/0 | {
"file_path": "transformers/docs/source/en/image_processors.md",
"repo_id": "transformers",
"token_count": 3596
} | 380 |
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to... | transformers/docs/source/en/llm_optims.md/0 | {
"file_path": "transformers/docs/source/en/llm_optims.md",
"repo_id": "transformers",
"token_count": 7181
} | 381 |
<!--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/output.md/0 | {
"file_path": "transformers/docs/source/en/main_classes/output.md",
"repo_id": "transformers",
"token_count": 1670
} | 382 |
<!--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/auto.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/auto.md",
"repo_id": "transformers",
"token_count": 1795
} | 383 |
<!--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/bit.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/bit.md",
"repo_id": "transformers",
"token_count": 1129
} | 384 |
<!--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/clip.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/clip.md",
"repo_id": "transformers",
"token_count": 1632
} | 385 |
<!--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/csm.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/csm.md",
"repo_id": "transformers",
"token_count": 4409
} | 386 |
<!--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/deit.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/deit.md",
"repo_id": "transformers",
"token_count": 2942
} | 387 |
<!--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/doge.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/doge.md",
"repo_id": "transformers",
"token_count": 1233
} | 388 |
<!--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 | {
"file_path": "transformers/docs/source/en/model_doc/fsmt.md",
"repo_id": "transformers",
"token_count": 766
} | 389 |
<!--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 | {
"file_path": "transformers/docs/source/en/model_doc/gpt2.md",
"repo_id": "transformers",
"token_count": 1969
} | 390 |
<!--Copyright 2025 The HuggingFace Team. All rights reserved.
Licensed under the MIT License; you may not use this file except in compliance with
the License.
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
an "AS IS" BASIS, WITHOUT WARRANTIES OR CON... | transformers/docs/source/en/model_doc/lightglue.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/lightglue.md",
"repo_id": "transformers",
"token_count": 1908
} | 391 |
<!--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/mamba.md/0 | {
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