text stringlengths 96 319k | id stringlengths 14 178 | metadata dict |
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#!/usr/bin/env python
# coding=utf-8
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/L... | smolagents/src/smolagents/local_python_executor.py/0 | {
"file_path": "smolagents/src/smolagents/local_python_executor.py",
"repo_id": "smolagents",
"token_count": 22987
} |
from unittest.mock import MagicMock, patch
from smolagents.e2b_executor import E2BExecutor
class TestE2BExecutor:
def test_e2b_executor_instantiation(self):
logger = MagicMock()
with patch("e2b_code_interpreter.Sandbox") as mock_sandbox:
mock_sandbox.return_value.commands.run.return_v... | smolagents/tests/test_e2b_executor.py/0 | {
"file_path": "smolagents/tests/test_e2b_executor.py",
"repo_id": "smolagents",
"token_count": 333
} |
use std::fs;
fn main() -> Result<(), Box<dyn std::error::Error>> {
println!("cargo:rerun-if-changed=../../proto/");
fs::create_dir_all("src/v2/pb").unwrap_or(());
let mut config = prost_build::Config::new();
config.protoc_arg("--experimental_allow_proto3_optional");
tonic_build::configure()
... | text-generation-inference/backends/client/build.rs/0 | {
"file_path": "text-generation-inference/backends/client/build.rs",
"repo_id": "text-generation-inference",
"token_count": 624
} |
set(TRT_INCLUDE_DIR ${TGI_TRTLLM_BACKEND_TRT_INCLUDE_DIR})
set(TRT_LIB_DIR ${TGI_TRTLLM_BACKEND_TRT_LIB_DIR})
set(USE_CXX11_ABI ON)
set(BUILD_PYT OFF)
set(BUILD_PYBIND OFF)
set(BUILD_MICRO_BENCHMARKS OFF)
set(BUILD_BENCHMARKS OFF)
set(BUILD_TESTS OFF)
set(CMAKE_CUDA_ARCHITECTURES ${TGI_TRTLLM_BACKEND_TARGET_CUDA_ARCH_... | text-generation-inference/backends/trtllm/cmake/trtllm.cmake/0 | {
"file_path": "text-generation-inference/backends/trtllm/cmake/trtllm.cmake",
"repo_id": "text-generation-inference",
"token_count": 976
} |
mod backend;
pub mod block_allocator;
mod client;
mod queue;
pub mod radix;
use crate::client::{ClientError, ShardedClient};
pub(crate) use backend::BackendV3;
use serde::Serialize;
use thiserror::Error;
use utoipa::ToSchema;
#[derive(Clone, Debug, Serialize, ToSchema)]
pub struct BackendInfo {
/// Mandatory
... | text-generation-inference/backends/v3/src/lib.rs/0 | {
"file_path": "text-generation-inference/backends/v3/src/lib.rs",
"repo_id": "text-generation-inference",
"token_count": 3087
} |
- sections:
- local: index
title: Text Generation Inference
- local: quicktour
title: Quick Tour
- local: supported_models
title: Supported Models
- local: installation_nvidia
title: Using TGI with Nvidia GPUs
- local: installation_amd
title: Using TGI with AMD GPUs
- local: installation... | text-generation-inference/docs/source/_toctree.yml/0 | {
"file_path": "text-generation-inference/docs/source/_toctree.yml",
"repo_id": "text-generation-inference",
"token_count": 864
} |
# Guidance
## What is Guidance?
Guidance is a feature that allows users to constrain the generation of a large language model with a specified grammar. This feature is particularly useful when you want to generate text that follows a specific structure or uses a specific set of words or produce output in a specific f... | text-generation-inference/docs/source/conceptual/guidance.md/0 | {
"file_path": "text-generation-inference/docs/source/conceptual/guidance.md",
"repo_id": "text-generation-inference",
"token_count": 1237
} |
# Multi-backend support
TGI (Text Generation Inference) offers flexibility by supporting multiple backends for serving large language models (LLMs).
With multi-backend support, you can choose the backend that best suits your needs,
whether you prioritize performance, ease of use, or compatibility with specific hardwar... | text-generation-inference/docs/source/multi_backend_support.md/0 | {
"file_path": "text-generation-inference/docs/source/multi_backend_support.md",
"repo_id": "text-generation-inference",
"token_count": 223
} |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [],
"seed": null,
"tokens": [
{
"id": 29946,
"logprob": -1.4765625,
"special": false,
"text": "4"
},
{
"id": 29906,
"logprob... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_grammar_llama/test_flash_llama_grammar_regex.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_grammar_llama/test_flash_llama_grammar_regex.json",
"repo_id": "text-generation-inference",
"token_count": 860
} |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [],
"seed": 0,
"tokens": [
{
"id": 1313,
"logprob": -2.3613281,
"special": false,
"text": "It"
},
{
"id": 3969,
"logprob": -... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_mixtral/test_flash_mixtral_all_params.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_mixtral/test_flash_mixtral_all_params.json",
"repo_id": "text-generation-inference",
"token_count": 858
} |
{
"details": {
"best_of_sequences": null,
"finish_reason": "stop_sequence",
"generated_tokens": 6,
"prefill": [],
"seed": 0,
"tokens": [
{
"id": 284,
"logprob": -0.28955078,
"special": false,
"text": " to"
},
{
"id": 3758,
"logp... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_phi/test_flash_phi_all_params.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_phi/test_flash_phi_all_params.json",
"repo_id": "text-generation-inference",
"token_count": 568
} |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [],
"seed": 0,
"tokens": [
{
"id": 288,
"logprob": -0.2854004,
"special": false,
"text": "ing"
},
{
"id": 264,
"logprob": -0... | text-generation-inference/integration-tests/models/__snapshots__/test_idefics2/test_flash_idefics2_next_all_params.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_idefics2/test_flash_idefics2_next_all_params.json",
"repo_id": "text-generation-inference",
"token_count": 860
} |
import pytest
@pytest.fixture(scope="module")
def compressed_tensors_w8an_handle(launcher):
with launcher(
"neuralmagic/Llama-3.2-1B-Instruct-FP8",
num_shard=2,
quantize="compressed-tensors",
) as handle:
yield handle
@pytest.fixture(scope="module")
async def compressed_tenso... | text-generation-inference/integration-tests/models/test_compressed_tensors_w8an_fp.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_compressed_tensors_w8an_fp.py",
"repo_id": "text-generation-inference",
"token_count": 1000
} |
import pytest
@pytest.fixture(scope="module")
def flash_llama_fp8_kv_cache_handle(launcher):
with launcher(
"neuralmagic/Meta-Llama-3-8B-Instruct-FP8-KV",
num_shard=2,
kv_cache_dtype="fp8_e4m3fn",
) as handle:
yield handle
@pytest.fixture(scope="module")
async def flash_llama... | text-generation-inference/integration-tests/models/test_flash_llama_fp8_kv_cache.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_flash_llama_fp8_kv_cache.py",
"repo_id": "text-generation-inference",
"token_count": 986
} |
import pytest
@pytest.fixture(scope="module")
def flash_phi35_moe_handle(launcher):
with launcher(
"microsoft/Phi-3.5-MoE-instruct",
num_shard=4,
) as handle:
yield handle
@pytest.fixture(scope="module")
async def flash_phi35_moe(flash_phi35_moe_handle):
await flash_phi35_moe_han... | text-generation-inference/integration-tests/models/test_flash_phi35_moe.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_flash_phi35_moe.py",
"repo_id": "text-generation-inference",
"token_count": 921
} |
import pytest
import asyncio
@pytest.fixture(scope="module")
def mllama_handle(launcher):
with launcher(
"meta-llama/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(... | 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": 1587
} |
pub fn get_cuda_capability() -> Option<(usize, usize)> {
use pyo3::prelude::*;
let py_get_capability = |py: Python| -> PyResult<(isize, isize)> {
let torch = py.import_bound("torch.cuda")?;
let get_device_capability = torch.getattr("get_device_capability")?;
get_device_capability.call0(... | text-generation-inference/launcher/src/gpu.rs/0 | {
"file_path": "text-generation-inference/launcher/src/gpu.rs",
"repo_id": "text-generation-inference",
"token_count": 350
} |
final: prev: {
# You can use this overlay to temporarily override packages for
# development. For permanent overrides, it's better to do this in
# our package flake:
#
# https://github.com/huggingface/text-generation-inference-nix
#
# Note that overriding packages that are in the transitive closure
# of... | text-generation-inference/nix/overlay.nix/0 | {
"file_path": "text-generation-inference/nix/overlay.nix",
"repo_id": "text-generation-inference",
"token_count": 633
} |
use crate::config::Config;
use clap::ValueEnum;
use csv::ReaderBuilder;
use reqwest::header::HeaderMap;
use serde::Serialize;
use std::{
fs::File,
io::{self, BufRead},
path::Path,
process::Command,
time::Duration,
};
use uuid::Uuid;
const TELEMETRY_URL: &str = "https://huggingface.co/api/telemetry/... | text-generation-inference/router/src/usage_stats.rs/0 | {
"file_path": "text-generation-inference/router/src/usage_stats.rs",
"repo_id": "text-generation-inference",
"token_count": 5315
} |
# Text Generation Inference Python gRPC Server
A Python gRPC server for Text Generation Inference
## Install
```shell
make install
```
## Run
```shell
make run-dev
```
| text-generation-inference/server/README.md/0 | {
"file_path": "text-generation-inference/server/README.md",
"repo_id": "text-generation-inference",
"token_count": 56
} |
// Adapted from turboderp exllama: https://github.com/turboderp/exllama
#ifndef _matrix_cuh
#define _matrix_cuh
#include <cuda_runtime.h>
#include <cuda_fp16.h>
class MatrixView_half
{
public:
const half* data;
const int height;
const int width;
__device__ __forceinline__ MatrixView_half(const half*... | text-generation-inference/server/exllama_kernels/exllama_kernels/matrix.cuh/0 | {
"file_path": "text-generation-inference/server/exllama_kernels/exllama_kernels/matrix.cuh",
"repo_id": "text-generation-inference",
"token_count": 5380
} |
#ifndef _qdq_4_cuh
#define _qdq_4_cuh
#include "qdq_util.cuh"
#include "../../config.h"
#if QMODE_4BIT == 1
// Permutation:
//
// 77775555 33331111 66664444 22220000
__forceinline__ __device__ void shuffle_4bit_8
(
uint32_t* q,
int stride
)
{
uint32_t qa = q[0];
uint32_t qb = 0;
#pragma unroll... | text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/quant/qdq_4.cuh/0 | {
"file_path": "text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/quant/qdq_4.cuh",
"repo_id": "text-generation-inference",
"token_count": 3279
} |
import pytest
import torch
from copy import copy
from transformers import AutoTokenizer
from text_generation_server.pb import generate_pb2
from text_generation_server.models.causal_lm import CausalLM, CausalLMBatch
@pytest.fixture(scope="session")
def default_causal_lm():
return CausalLM.fallback("gpt2")
@pyt... | text-generation-inference/server/tests/models/test_causal_lm.py/0 | {
"file_path": "text-generation-inference/server/tests/models/test_causal_lm.py",
"repo_id": "text-generation-inference",
"token_count": 5390
} |
import torch
from typing import Dict, Optional, TypeVar
from text_generation_server.models.types import Batch
B = TypeVar("B", bound=Batch)
class Cache:
def __init__(self):
self.cache: Dict[int, B] = {}
def pop(self, batch_id: int) -> Optional[B]:
return self.cache.pop(batch_id, None)
... | text-generation-inference/server/text_generation_server/cache.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/cache.py",
"repo_id": "text-generation-inference",
"token_count": 359
} |
from dataclasses import dataclass
import bitsandbytes as bnb
import torch
from bitsandbytes.nn import Int8Params, Params4bit
from text_generation_server.utils.weights import UnquantizedWeight
@dataclass
class BNBWeight(UnquantizedWeight):
weight: torch.Tensor
def get_linear(self, bias: torch.Tensor):
... | text-generation-inference/server/text_generation_server/layers/bnb.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/layers/bnb.py",
"repo_id": "text-generation-inference",
"token_count": 1825
} |
import time
import torch.nn as nn
import math
import json
import os
import torch
import transformers
from texttable import Texttable
from transformers import AutoModelForCausalLM, AutoConfig, AutoTokenizer
from huggingface_hub import HfApi
from accelerate import init_empty_weights
from text_generation_server.utils imp... | text-generation-inference/server/text_generation_server/layers/gptq/quantize.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/layers/gptq/quantize.py",
"repo_id": "text-generation-inference",
"token_count": 16305
} |
from dataclasses import dataclass
from typing import List, Optional
import torch
import torch.nn as nn
from text_generation_server.utils.import_utils import SYSTEM
from text_generation_server.utils.weights import Weights
from text_generation_server.layers.marlin.gptq import (
GPTQMarlinWeight,
GPTQMarlinWeigh... | text-generation-inference/server/text_generation_server/layers/moe/gptq_marlin.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/layers/moe/gptq_marlin.py",
"repo_id": "text-generation-inference",
"token_count": 3509
} |
def load_text_model(prefix, config, weights, name=None):
if config.model_type == "llama":
from text_generation_server.models.custom_modeling.flash_llama_modeling import (
FlashLlamaForCausalLM,
)
return FlashLlamaForCausalLM(prefix, config, weights, name=name)
elif config.mo... | text-generation-inference/server/text_generation_server/models/custom_modeling/vlm.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/models/custom_modeling/vlm.py",
"repo_id": "text-generation-inference",
"token_count": 868
} |
import grpc
from opentelemetry import trace
from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter
from opentelemetry.instrumentation.grpc._aio_server import (
OpenTelemetryAioServerInterceptor,
)
from opentelemetry.semconv.trace import SpanAttributes
from opentelemetry.sdk.resources im... | text-generation-inference/server/text_generation_server/tracing.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/tracing.py",
"repo_id": "text-generation-inference",
"token_count": 969
} |
# Origin: https://github.com/predibase/lorax
# Path: lorax/server/lorax_server/utils/sgmv.py
# License: Apache License Version 2.0, January 2004
import os
import warnings
from functools import lru_cache
from typing import List, Tuple
import torch
import torch.nn.functional as F
try:
import punica_kernels ... | text-generation-inference/server/text_generation_server/utils/sgmv.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/utils/sgmv.py",
"repo_id": "text-generation-inference",
"token_count": 3651
} |
extern crate tokenizers as tk;
use crate::encoding::*;
use crate::tokenizer::Tokenizer;
use napi::bindgen_prelude::*;
use tk::tokenizer::{EncodeInput, Encoding};
pub struct EncodeTask<'s> {
pub tokenizer: Tokenizer,
pub input: Option<EncodeInput<'s>>,
pub add_special_tokens: bool,
}
impl Task for EncodeTask<'s... | tokenizers/bindings/node/src/tasks/tokenizer.rs/0 | {
"file_path": "tokenizers/bindings/node/src/tasks/tokenizer.rs",
"repo_id": "tokenizers",
"token_count": 1295
} |
from typing import List
import jieba
from tokenizers import NormalizedString, PreTokenizedString, Regex, Tokenizer
from tokenizers.decoders import Decoder
from tokenizers.models import BPE
from tokenizers.normalizers import Normalizer
from tokenizers.pre_tokenizers import PreTokenizer
class JiebaPreTokenizer:
de... | tokenizers/bindings/python/examples/custom_components.py/0 | {
"file_path": "tokenizers/bindings/python/examples/custom_components.py",
"repo_id": "tokenizers",
"token_count": 1292
} |
import json
import os
from typing import Iterator, List, Optional, Union, Tuple
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.models import Unigram
from .base_tokenizer import BaseTokenizer
class SentencePieceUnigramTokenizer(BaseTokenizer):
... | tokenizers/bindings/python/py_src/tokenizers/implementations/sentencepiece_unigram.py/0 | {
"file_path": "tokenizers/bindings/python/py_src/tokenizers/implementations/sentencepiece_unigram.py",
"repo_id": "tokenizers",
"token_count": 3405
} |
import transformers
from tokenizers.implementations import SentencePieceUnigramTokenizer, BaseTokenizer
from tokenizers.processors import TemplateProcessing
from tokenizers.models import Unigram, BPE
from tokenizers import decoders
from tokenizers import Tokenizer, Regex
from tokenizers.normalizers import (
StripAc... | tokenizers/bindings/python/scripts/convert.py/0 | {
"file_path": "tokenizers/bindings/python/scripts/convert.py",
"repo_id": "tokenizers",
"token_count": 6304
} |
use std::marker::PhantomData;
use std::sync::{Arc, Mutex};
mod iterators;
mod normalization;
mod pretokenization;
mod regex;
pub mod serde_pyo3;
pub use iterators::*;
pub use normalization::*;
pub use pretokenization::*;
pub use regex::*;
// RefMut utils
pub trait DestroyPtr {
fn destroy(&mut self);
}
pub stru... | tokenizers/bindings/python/src/utils/mod.rs/0 | {
"file_path": "tokenizers/bindings/python/src/utils/mod.rs",
"repo_id": "tokenizers",
"token_count": 752
} |
import copy
import os
import pickle
import pytest
from tokenizers import (
AddedToken,
SentencePieceUnigramTokenizer,
Tokenizer,
models,
normalizers,
pre_tokenizers,
trainers,
)
from ..utils import data_dir, train_files
class TestBpeTrainer:
def test_can_modify(self):
traine... | tokenizers/bindings/python/tests/bindings/test_trainers.py/0 | {
"file_path": "tokenizers/bindings/python/tests/bindings/test_trainers.py",
"repo_id": "tokenizers",
"token_count": 4958
} |
# Added Tokens
<tokenizerslangcontent>
<python>
## AddedToken
[[autodoc]] tokenizers.AddedToken
- content
- lstrip
- normalized
- rstrip
- single_word
</python>
<rust>
The Rust API Reference is available directly on the [Docs.rs](https://docs.rs/tokenizers/latest/tokenizers/) website.
</rust>
<nod... | tokenizers/docs/source-doc-builder/api/added-tokens.mdx/0 | {
"file_path": "tokenizers/docs/source-doc-builder/api/added-tokens.mdx",
"repo_id": "tokenizers",
"token_count": 134
} |
# 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.
## Build a tokenizer from scratch
To illustrate how fast the 🤗 Tokenizers library is, let's train a new
tokenizer on [wikitext-... | tokenizers/docs/source-doc-builder/quicktour.mdx/0 | {
"file_path": "tokenizers/docs/source-doc-builder/quicktour.mdx",
"repo_id": "tokenizers",
"token_count": 7936
} |
Components
====================================================================================================
When building a Tokenizer, you can attach various types of components to this Tokenizer in order
to customize its behavior. This page lists most provided components.
.. _normalizers:
.. entities:: python
... | tokenizers/docs/source/components.rst/0 | {
"file_path": "tokenizers/docs/source/components.rst",
"repo_id": "tokenizers",
"token_count": 4223
} |
<p align="center">
<br>
<img src="https://huggingface.co/landing/assets/tokenizers/tokenizers-logo.png" width="600"/>
<br>
<p>
<p align="center">
<img alt="Build" src="https://github.com/huggingface/tokenizers/workflows/Rust/badge.svg">
<a href="https://github.com/huggingface/tokenizers/blob/master/... | tokenizers/tokenizers/README.tpl/0 | {
"file_path": "tokenizers/tokenizers/README.tpl",
"repo_id": "tokenizers",
"token_count": 259
} |
pub mod bpe;
pub mod byte_fallback;
pub mod ctc;
pub mod fuse;
pub mod sequence;
pub mod strip;
pub mod wordpiece;
// Re-export these as decoders
pub use super::pre_tokenizers::byte_level;
pub use super::pre_tokenizers::metaspace;
use serde::{Deserialize, Deserializer, Serialize};
use crate::decoders::bpe::BPEDecode... | tokenizers/tokenizers/src/decoders/mod.rs/0 | {
"file_path": "tokenizers/tokenizers/src/decoders/mod.rs",
"repo_id": "tokenizers",
"token_count": 4660
} |
use std::collections::HashMap;
use std::hash::Hash;
#[derive(Default)]
pub struct TrieBuilder<Label> {
trie: Trie<Label>,
}
impl<Label: Eq + Hash + Copy> TrieBuilder<Label> {
pub fn push(&mut self, element: &[Label]) {
self.trie.push(element);
}
pub fn build(self) -> Trie<Label> {
sel... | tokenizers/tokenizers/src/models/unigram/trie.rs/0 | {
"file_path": "tokenizers/tokenizers/src/models/unigram/trie.rs",
"repo_id": "tokenizers",
"token_count": 944
} |
use crate::tokenizer::{PreTokenizedString, PreTokenizer, Result, SplitDelimiterBehavior};
use crate::utils::macro_rules_attribute;
use unicode_categories::UnicodeCategories;
fn is_bert_punc(x: char) -> bool {
char::is_ascii_punctuation(&x) || x.is_punctuation()
}
#[derive(Copy, Clone, Debug, PartialEq, Eq)]
#[mac... | tokenizers/tokenizers/src/pre_tokenizers/bert.rs/0 | {
"file_path": "tokenizers/tokenizers/src/pre_tokenizers/bert.rs",
"repo_id": "tokenizers",
"token_count": 1460
} |
use crate::processors::PostProcessorWrapper;
use crate::tokenizer::{Encoding, PostProcessor, Result};
use crate::utils::macro_rules_attribute;
use serde::{Deserialize, Serialize};
#[derive(Clone, Debug, PartialEq, Eq)]
#[macro_rules_attribute(impl_serde_type!)]
pub struct Sequence {
processors: Vec<PostProcessorWr... | tokenizers/tokenizers/src/processors/sequence.rs/0 | {
"file_path": "tokenizers/tokenizers/src/processors/sequence.rs",
"repo_id": "tokenizers",
"token_count": 2672
} |
//!
//! This module defines helpers to allow optional Rayon usage.
//!
use rayon::iter::IterBridge;
use rayon::prelude::*;
use rayon_cond::CondIterator;
use std::sync::atomic::AtomicBool;
use std::sync::atomic::AtomicU8;
use std::sync::atomic::Ordering;
// Re-export rayon current_num_threads
pub use rayon::current_nu... | tokenizers/tokenizers/src/utils/parallelism.rs/0 | {
"file_path": "tokenizers/tokenizers/src/utils/parallelism.rs",
"repo_id": "tokenizers",
"token_count": 3698
} |
To install via [NPM](https://www.npmjs.com/package/@huggingface/transformers), run:
```bash
npm i @huggingface/transformers
```
Alternatively, you can use it in vanilla JS, without any bundler, by using a CDN or static hosting. For example, using [ES Modules](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Gu... | transformers.js/docs/snippets/2_installation.snippet/0 | {
"file_path": "transformers.js/docs/snippets/2_installation.snippet",
"repo_id": "transformers.js",
"token_count": 176
} |
import Chart from 'chart.js/auto';
import Prism from 'prismjs';
// Import code and styles for supported languages
import 'prismjs/components/prism-javascript';
import 'prismjs/components/prism-python';
import 'prismjs/components/prism-markdown';
import 'prismjs/components/prism-clike';
import 'prismjs/themes/prism.c... | transformers.js/examples/demo-site/src/main.js/0 | {
"file_path": "transformers.js/examples/demo-site/src/main.js",
"repo_id": "transformers.js",
"token_count": 9224
} |
{
"name": "electron",
"productName": "electron",
"version": "1.0.0",
"description": "Transformers.js sample Electron application",
"main": "src/index.js",
"scripts": {
"start": "electron-forge start",
"package": "electron-forge package",
"make": "electron-forge make",
"publish": "electron-fo... | transformers.js/examples/electron/package.json/0 | {
"file_path": "transformers.js/examples/electron/package.json",
"repo_id": "transformers.js",
"token_count": 361
} |
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Transformers.js | Sample Browser Extension</title>
<!-- Load styles -->
<link rel="stylesheet" href... | transformers.js/examples/extension/src/popup.html/0 | {
"file_path": "transformers.js/examples/extension/src/popup.html",
"repo_id": "transformers.js",
"token_count": 246
} |
import { pipeline } from '@xenova/transformers';
import wavefile from 'wavefile';
// Load model
let transcriber = await pipeline('automatic-speech-recognition', 'Xenova/whisper-tiny.en');
// Load audio data
let url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/jfk.wav';
let buffer = Buff... | transformers.js/examples/node-audio-processing/index.js/0 | {
"file_path": "transformers.js/examples/node-audio-processing/index.js",
"repo_id": "transformers.js",
"token_count": 479
} |
import { pipeline } from '@xenova/transformers';
/**
* This class uses the Singleton pattern to ensure that only one instance of the
* pipeline is loaded. This is because loading the pipeline is an expensive
* operation and we don't want to do it every time we want to translate a sentence.
*/
class MyTranslationP... | transformers.js/examples/react-translator/src/worker.js/0 | {
"file_path": "transformers.js/examples/react-translator/src/worker.js",
"repo_id": "transformers.js",
"token_count": 614
} |
# Semantic Image Search
This example shows you how to use Transformers.js to create a semantic image search engine. Check out the demo [here](https://huggingface.co/spaces/Xenova/semantic-image-search).
![Semantic Image Search Demo](https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/semantic-im... | transformers.js/examples/semantic-image-search/README.md/0 | {
"file_path": "transformers.js/examples/semantic-image-search/README.md",
"repo_id": "transformers.js",
"token_count": 1129
} |
'use client'
import { useState } from 'react'
import { Modal } from './components/Modal';
import { SearchBar } from './components/SearchBar';
import { ImageGrid } from './components/ImageGrid';
export default function Home() {
// Application state
const [images, setImages] = useState(null);
const [currentImage... | transformers.js/examples/semantic-image-search/src/app/page.js/0 | {
"file_path": "transformers.js/examples/semantic-image-search/src/app/page.js",
"repo_id": "transformers.js",
"token_count": 345
} |
// Although not strictly necessary, we delegate the tokenization to a worker thread to avoid
// any potential issues with the tokenizer blocking the main thread (especially for large inputs).
import { env, AutoTokenizer } from '@xenova/transformers'
env.allowLocalModels = false;
// This is a map of all the tokenizer... | transformers.js/examples/tokenizer-playground/src/worker.js/0 | {
"file_path": "transformers.js/examples/tokenizer-playground/src/worker.js",
"repo_id": "transformers.js",
"token_count": 1112
} |
import './style.css';
import { env, AutoModel, AutoProcessor, RawImage } from '@xenova/transformers';
env.backends.onnx.wasm.wasmPaths = 'https://cdn.jsdelivr.net/npm/onnxruntime-web@1.17.1/dist/';
env.backends.onnx.wasm.numThreads = 1;
// Reference the elements that we will need
const status = document.getElementBy... | transformers.js/examples/webgpu-video-background-removal/main.js/0 | {
"file_path": "transformers.js/examples/webgpu-video-background-removal/main.js",
"repo_id": "transformers.js",
"token_count": 1573
} |
import { FEATURE_EXTRACTOR_NAME } from "../utils/constants.js";
import { Callable } from "../utils/generic.js";
import { getModelJSON } from "../utils/hub.js";
/**
* Base class for feature extractors.
*/
export class FeatureExtractor extends Callable {
/**
* Constructs a new FeatureExtractor instance.
... | transformers.js/src/base/feature_extraction_utils.js/0 | {
"file_path": "transformers.js/src/base/feature_extraction_utils.js",
"repo_id": "transformers.js",
"token_count": 822
} |
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": 4606
} |
import { FeatureExtractor, validate_audio_inputs } from '../../base/feature_extraction_utils.js';
import { Tensor } from '../../utils/tensor.js';
export class MoonshineFeatureExtractor extends FeatureExtractor {
/**
* Asynchronously extracts input values from a given audio using the provided configuration.
... | transformers.js/src/models/moonshine/feature_extraction_moonshine.js/0 | {
"file_path": "transformers.js/src/models/moonshine/feature_extraction_moonshine.js",
"repo_id": "transformers.js",
"token_count": 364
} |
import {
ImageProcessor,
} from "../../base/image_processors_utils.js";
import { calculateDimensions } from "../../utils/core.js";
import {
interpolate_4d,
Tensor,
} from "../../utils/tensor.js";
/**
* @typedef {object} SamImageProcessorResult
* @property {Tensor} pixel_values
* @property {import("..... | transformers.js/src/models/sam/image_processing_sam.js/0 | {
"file_path": "transformers.js/src/models/sam/image_processing_sam.js",
"repo_id": "transformers.js",
"token_count": 4498
} |
const WHISPER_LANGUAGES = [
["en", "english"],
["zh", "chinese"],
["de", "german"],
["es", "spanish"],
["ru", "russian"],
["ko", "korean"],
["fr", "french"],
["ja", "japanese"],
["pt", "portuguese"],
["tr", "turkish"],
["pl", "polish"],
["ca", "catalan"],
["nl", "du... | transformers.js/src/models/whisper/common_whisper.js/0 | {
"file_path": "transformers.js/src/models/whisper/common_whisper.js",
"repo_id": "transformers.js",
"token_count": 1848
} |
/**
* @file Utility functions to interact with the Hugging Face Hub (https://huggingface.co/models)
*
* @module utils/hub
*/
import fs from 'fs';
import path from 'path';
import { env } from '../env.js';
import { dispatchCallback } from './core.js';
/**
* @typedef {Object} PretrainedOptions Options for loadin... | transformers.js/src/utils/hub.js/0 | {
"file_path": "transformers.js/src/utils/hub.js",
"repo_id": "transformers.js",
"token_count": 10053
} |
import { AutoImageProcessor, DPTFeatureExtractor, DPTImageProcessor } 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 () => {
// DPTFeatureExtractor
describe("DPTFeatureE... | transformers.js/tests/models/dpt/test_image_processing_dpt.js/0 | {
"file_path": "transformers.js/tests/models/dpt/test_image_processing_dpt.js",
"repo_id": "transformers.js",
"token_count": 1111
} |
import { MgpstrProcessor, MgpstrForSceneTextRecognition } from "../../../src/transformers.js";
import { load_cached_image } from "../../asset_cache.js";
import { MAX_MODEL_LOAD_TIME, MAX_TEST_EXECUTION_TIME, MAX_MODEL_DISPOSE_TIME, DEFAULT_MODEL_OPTIONS } from "../../init.js";
export default () => {
describe("Mgpst... | transformers.js/tests/models/mgp_str/test_modeling_mgp_str.js/0 | {
"file_path": "transformers.js/tests/models/mgp_str/test_modeling_mgp_str.js",
"repo_id": "transformers.js",
"token_count": 1680
} |
import { AutoProcessor, PaliGemmaProcessor } 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 () => {
const model_id = "hf-internal-testing/tiny-random-PaliGemmaForCondition... | transformers.js/tests/models/paligemma/test_processor_paligemma.js/0 | {
"file_path": "transformers.js/tests/models/paligemma/test_processor_paligemma.js",
"repo_id": "transformers.js",
"token_count": 709
} |
import { pipeline, AutomaticSpeechRecognitionPipeline } 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 = "automatic-speech-recognition";
export default () => {
describe("Automatic Speech R... | transformers.js/tests/pipelines/test_pipelines_automatic_speech_recognition.js/0 | {
"file_path": "transformers.js/tests/pipelines/test_pipelines_automatic_speech_recognition.js",
"repo_id": "transformers.js",
"token_count": 2373
} |
import { pipeline, TextToAudioPipeline } 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 = "text-to-audio";
export default () => {
describe("Text to Audio", () => {
const model_id = "Xe... | transformers.js/tests/pipelines/test_pipelines_text_to_audio.js/0 | {
"file_path": "transformers.js/tests/pipelines/test_pipelines_text_to_audio.js",
"repo_id": "transformers.js",
"token_count": 492
} |
import { Tensor, cat, stack, layer_norm, ones_like, zeros_like, full_like, rand, std_mean } from "../../src/transformers.js";
import { init } from "../init.js";
import { compare } from "../test_utils.js";
init();
describe("Tensor operations", () => {
describe("cat", () => {
it("should concatenate on dim=0", () ... | transformers.js/tests/utils/tensor.test.js/0 | {
"file_path": "transformers.js/tests/utils/tensor.test.js",
"repo_id": "transformers.js",
"token_count": 9122
} |
# Copyright 2024 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | transformers/benchmark/benchmark.py/0 | {
"file_path": "transformers/benchmark/benchmark.py",
"repo_id": "transformers",
"token_count": 5440
} |
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 libgl1-mesa-glx libgl1 g++ tesseract-ocr
ENV UV_PYTHON=/usr/local/bin/python
RUN pip --no-cache-dir install uv && uv venv && uv pip install --no-cache-dir -U pip setupto... | transformers/docker/exotic-models.dockerfile/0 | {
"file_path": "transformers/docker/exotic-models.dockerfile",
"repo_id": "transformers",
"token_count": 468
} |
# https://docs.nvidia.com/deeplearning/frameworks/pytorch-release-notes/rel-23-11.html#rel-23-11
FROM nvcr.io/nvidia/pytorch:23.11-py3
LABEL maintainer="Hugging Face"
ARG DEBIAN_FRONTEND=noninteractive
# Example: `cu102`, `cu113`, etc.
ARG CUDA='cu121'
RUN apt -y update
RUN apt install -y libaio-dev
RUN python3 -m p... | transformers/docker/transformers-pytorch-deepspeed-nightly-gpu/Dockerfile/0 | {
"file_path": "transformers/docker/transformers-pytorch-deepspeed-nightly-gpu/Dockerfile",
"repo_id": "transformers",
"token_count": 1032
} |
# تحميل نماذج مدربة مسبقًا باستخدام AutoClass
لم ترغب في إنشاء محول معماري لمؤشر الترابط الخاص بك، فهناك العديد من محولات المعمارية المختلفة التي يمكنك الاختيار من بينها. كجزء من الفلسفة الأساسية لـ 🤗 Transformers لجعل المكتبة سهلة وبسيطة ومرنة، فإن فئة `AutoClass` تستدل تلقائيًا وتحمّل البنية الصحيحة من نسخة نموذج (M... | transformers/docs/source/ar/autoclass_tutorial.md/0 | {
"file_path": "transformers/docs/source/ar/autoclass_tutorial.md",
"repo_id": "transformers",
"token_count": 5440
} |
# شارك نموذجك مع العالم
أظهرت آخر درسين تعليميين كيفية ضبط نموذج بدقة باستخدام PyTorch و Keras و 🤗 Accelerate لعمليات التهيئة الموزعة. والخطوة التالية هي مشاركة نموذجك مع المجتمع! في Hugging Face، نؤمن بالمشاركة المفتوحة للمعرفة والموارد لتمكين الجميع من الاستفادة من الذكاء الاصطناعي. ونشجعك على مشاركة نموذجك مع المج... | transformers/docs/source/ar/model_sharing.md/0 | {
"file_path": "transformers/docs/source/ar/model_sharing.md",
"repo_id": "transformers",
"token_count": 6706
} |
# ما الذي تستطيع مكتبة 🤗 Transformers القيام به؟
مكتبة 🤗 Transformers هي مجموعة من النماذج المُدرّبة مسبقًا الأفضل في فئتها لمهام معالجة اللغة الطبيعية (NLP)، ورؤية الحاسوب، ومعالجة الصوت والكلام. لا تحتوي المكتبة فقط على نماذج المحولات (Transformer) فحسب، بل تشمل أيضًا نماذج أخرى لا تعتمد على المحولات مثل الشبكات ا... | transformers/docs/source/ar/task_summary.md/0 | {
"file_path": "transformers/docs/source/ar/task_summary.md",
"repo_id": "transformers",
"token_count": 14746
} |
# استكشاف الأخطاء وإصلاحها
تحدث الأخطاء أحيانًا، لكننا هنا للمساعدة! يغطي هذا الدليل بعض المشكلات الأكثر شيوعًا التي واجهناها وكيفية حلها. مع ذلك، لا يُقصد بهذا الدليل أن يكون مجموعة شاملة لكل مشكلات 🤗 Transformers. لمزيد من المساعدة في استكشاف مشكلتك وإصلاحها، جرب ما يلي:
<Youtube id="S2EEG3JIt2A"/>
1. اطلب المساع... | transformers/docs/source/ar/troubleshooting.md/0 | {
"file_path": "transformers/docs/source/ar/troubleshooting.md",
"repo_id": "transformers",
"token_count": 5400
} |
<!--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/de/quicktour.md/0 | {
"file_path": "transformers/docs/source/de/quicktour.md",
"repo_id": "transformers",
"token_count": 7324
} |
<!--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/big_models.md/0 | {
"file_path": "transformers/docs/source/en/big_models.md",
"repo_id": "transformers",
"token_count": 3022
} |
<!--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... | transformers/docs/source/en/main_classes/backbones.md/0 | {
"file_path": "transformers/docs/source/en/main_classes/backbones.md",
"repo_id": "transformers",
"token_count": 689
} |
<!--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/beit.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/beit.md",
"repo_id": "transformers",
"token_count": 3501
} |
<!--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/convbert.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/convbert.md",
"repo_id": "transformers",
"token_count": 1393
} |
<!--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... | transformers/docs/source/en/model_doc/efficientnet.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/efficientnet.md",
"repo_id": "transformers",
"token_count": 725
} |
<!--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/fnet.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/fnet.md",
"repo_id": "transformers",
"token_count": 1150
} |
<!--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/gpt_neox_japanese.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/gpt_neox_japanese.md",
"repo_id": "transformers",
"token_count": 1075
} |
<!--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/lilt.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/lilt.md",
"repo_id": "transformers",
"token_count": 1291
} |
<!--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/marian.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/marian.md",
"repo_id": "transformers",
"token_count": 3062
} |
<!--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... | transformers/docs/source/en/model_doc/mms.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/mms.md",
"repo_id": "transformers",
"token_count": 4924
} |
<!--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/rembert.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/rembert.md",
"repo_id": "transformers",
"token_count": 1363
} |
<!--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/vit_mae.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/vit_mae.md",
"repo_id": "transformers",
"token_count": 2432
} |
<!--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/xlm-roberta-xl.md/0 | {
"file_path": "transformers/docs/source/en/model_doc/xlm-roberta-xl.md",
"repo_id": "transformers",
"token_count": 969
} |
<!---
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 ... | transformers/docs/source/en/performance.md/0 | {
"file_path": "transformers/docs/source/en/performance.md",
"repo_id": "transformers",
"token_count": 966
} |
<!--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/quantization/higgs.md/0 | {
"file_path": "transformers/docs/source/en/quantization/higgs.md",
"repo_id": "transformers",
"token_count": 1149
} |
<!--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... | transformers/docs/source/en/tasks/image_captioning.md/0 | {
"file_path": "transformers/docs/source/en/tasks/image_captioning.md",
"repo_id": "transformers",
"token_count": 2730
} |
<!--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/torchscript.md/0 | {
"file_path": "transformers/docs/source/en/torchscript.md",
"repo_id": "transformers",
"token_count": 2742
} |
<!--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/es/debugging.md/0 | {
"file_path": "transformers/docs/source/es/debugging.md",
"repo_id": "transformers",
"token_count": 5532
} |
<!--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/es/quicktour.md/0 | {
"file_path": "transformers/docs/source/es/quicktour.md",
"repo_id": "transformers",
"token_count": 6360
} |
# docstyle-ignore
INSTALL_CONTENT = """
# Installazione di Transformers
! pip install transformers datasets evaluate accelerate
# Per installare dalla fonte invece dell'ultima versione rilasciata, commenta il comando sopra e
# rimuovi la modalità commento al comando seguente.
# ! pip install git+https://github.com/hugg... | transformers/docs/source/it/_config.py/0 | {
"file_path": "transformers/docs/source/it/_config.py",
"repo_id": "transformers",
"token_count": 190
} |
<!--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/it/multilingual.md/0 | {
"file_path": "transformers/docs/source/it/multilingual.md",
"repo_id": "transformers",
"token_count": 3202
} |
<!--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... | transformers/docs/source/ja/hpo_train.md/0 | {
"file_path": "transformers/docs/source/ja/hpo_train.md",
"repo_id": "transformers",
"token_count": 2838
} |
<!--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/ja/model_doc/albert.md/0 | {
"file_path": "transformers/docs/source/ja/model_doc/albert.md",
"repo_id": "transformers",
"token_count": 2960
} |
<!--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/ja/model_doc/bigbird_pegasus.md/0 | {
"file_path": "transformers/docs/source/ja/model_doc/bigbird_pegasus.md",
"repo_id": "transformers",
"token_count": 2264
} |
<!--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/ja/model_doc/clip.md/0 | {
"file_path": "transformers/docs/source/ja/model_doc/clip.md",
"repo_id": "transformers",
"token_count": 4574
} |
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