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# Using TGI with Nvidia GPUs TGI optimized models are supported on NVIDIA [H100](https://www.nvidia.com/en-us/data-center/h100/), [A100](https://www.nvidia.com/en-us/data-center/a100/), [A10G](https://www.nvidia.com/en-us/data-center/products/a10-gpu/) and [T4](https://www.nvidia.com/en-us/data-center/tesla-t4/) GPUs ...
text-generation-inference/docs/source/installation_nvidia.md/0
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from typing import Any, Dict, Generator from _pytest.fixtures import SubRequest from huggingface_hub import AsyncInferenceClient import pytest def pytest_configure(config): config.addinivalue_line( "markers", "gaudi_all_models: mark test to run with all models" ) # The "args" values in TEST_CONFIGS ...
text-generation-inference/integration-tests/gaudi/test_gaudi_generate.py/0
{ "file_path": "text-generation-inference/integration-tests/gaudi/test_gaudi_generate.py", "repo_id": "text-generation-inference", "token_count": 5095 }
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{ "choices": [ { "finish_reason": "length", "index": 0, "logprobs": null, "text": " A Beginner’s Guide\nDeep learning is a subset" } ], "created": 1741264812, "id": "", "model": "meta-llama/Llama-3.1-8B-Instruct", "object": "text_completion", "system_fingerprint": "3.1.2-de...
text-generation-inference/integration-tests/models/__snapshots__/test_completion_prompts/test_flash_llama_completion_single_prompt.json/0
{ "file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_completion_prompts/test_flash_llama_completion_single_prompt.json", "repo_id": "text-generation-inference", "token_count": 209 }
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{ "details": { "best_of_sequences": null, "finish_reason": "eos_token", "generated_tokens": 30, "prefill": [], "seed": null, "tokens": [ { "id": 6377, "logprob": -0.14916992, "special": false, "text": "{\"" }, { "id": 29888, "lo...
text-generation-inference/integration-tests/models/__snapshots__/test_flash_grammar_llama/test_flash_llama_grammar_json.json/0
{ "file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_grammar_llama/test_flash_llama_grammar_json.json", "repo_id": "text-generation-inference", "token_count": 2413 }
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{ "details": { "best_of_sequences": null, "finish_reason": "length", "generated_tokens": 10, "prefill": [], "seed": null, "tokens": [ { "id": 198, "logprob": -2.5742188, "special": false, "text": "\n" }, { "id": 262, "logprob": ...
text-generation-inference/integration-tests/models/__snapshots__/test_flash_llama_gptq/test_flash_llama_gptq.json/0
{ "file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_llama_gptq/test_flash_llama_gptq.json", "repo_id": "text-generation-inference", "token_count": 883 }
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{ "details": { "best_of_sequences": null, "finish_reason": "length", "generated_tokens": 20, "prefill": [], "seed": null, "tokens": [ { "id": 108, "logprob": -0.48046875, "special": false, "text": "\n" }, { "id": 30234, "logprob...
text-generation-inference/integration-tests/models/__snapshots__/test_flash_pali_gemma2/test_flash_pali_gemma_image.json/0
{ "file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_pali_gemma2/test_flash_pali_gemma_image.json", "repo_id": "text-generation-inference", "token_count": 1628 }
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{ "choices": [ { "finish_reason": "stop", "index": 0, "logprobs": null, "message": { "content": "The image depicts an anthropomorphic rabbit, wearing a spacesuit, standing in a barren, rocky landscape that resembles the surface of another planet, possibly Mars. The rabbit has a red...
text-generation-inference/integration-tests/models/__snapshots__/test_flash_qwen2_vl/test_flash_qwen2_vl_simple.json/0
{ "file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_qwen2_vl/test_flash_qwen2_vl_simple.json", "repo_id": "text-generation-inference", "token_count": 353 }
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{ "details": { "best_of_sequences": null, "finish_reason": "stop_sequence", "generated_tokens": 6, "prefill": [], "seed": 0, "tokens": [ { "id": 13, "logprob": -1.0654297, "special": false, "text": "\n" }, { "id": 1014, "logprob...
text-generation-inference/integration-tests/models/__snapshots__/test_llava_next/test_flash_llava_next_all_params.json/0
{ "file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_llava_next/test_flash_llava_next_all_params.json", "repo_id": "text-generation-inference", "token_count": 563 }
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[ { "details": { "best_of_sequences": null, "finish_reason": "eos_token", "generated_tokens": 6, "prefill": [ { "id": 0, "logprob": null, "text": "<pad>" } ], "seed": null, "tokens": [ { "id": 259, ...
text-generation-inference/integration-tests/models/__snapshots__/test_mt0_base/test_mt0_base_load.json/0
{ "file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_mt0_base/test_mt0_base_load.json", "repo_id": "text-generation-inference", "token_count": 2874 }
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import pytest @pytest.fixture(scope="module") def bloom_560m_sharded_handle(launcher): with launcher("bigscience/bloom-560m", num_shard=2) as handle: yield handle @pytest.fixture(scope="module") async def bloom_560m_sharded(bloom_560m_sharded_handle): await bloom_560m_sharded_handle.health(240) ...
text-generation-inference/integration-tests/models/test_bloom_560m_sharded.py/0
{ "file_path": "text-generation-inference/integration-tests/models/test_bloom_560m_sharded.py", "repo_id": "text-generation-inference", "token_count": 527 }
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import base64 from io import BytesIO from PIL import Image import pytest @pytest.fixture(scope="module") def flash_gemma3_handle(launcher): with launcher("google/gemma-3-4b-it", num_shard=2) as handle: yield handle @pytest.fixture(scope="module") async def flash_gemma3(flash_gemma3_handle): await f...
text-generation-inference/integration-tests/models/test_flash_gemma3.py/0
{ "file_path": "text-generation-inference/integration-tests/models/test_flash_gemma3.py", "repo_id": "text-generation-inference", "token_count": 2840 }
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import pytest @pytest.fixture(scope="module") def flash_mixtral_awq_handle(launcher): with launcher("casperhansen/mixtral-instruct-awq", num_shard=2) as handle: yield handle @pytest.fixture(scope="module") async def flash_mixtral_awq(flash_mixtral_awq_handle): await flash_mixtral_awq_handle.health(3...
text-generation-inference/integration-tests/models/test_flash_mixtral_awq.py/0
{ "file_path": "text-generation-inference/integration-tests/models/test_flash_mixtral_awq.py", "repo_id": "text-generation-inference", "token_count": 898 }
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import pytest import json from text_generation.types import GrammarType @pytest.fixture(scope="module") def non_flash_llama_grammar_handle(launcher): with launcher( "TinyLlama/TinyLlama-1.1B-Chat-v1.0", num_shard=1, disable_grammar_support=False, use_flash_attention=False, ) a...
text-generation-inference/integration-tests/models/test_grammar_llama.py/0
{ "file_path": "text-generation-inference/integration-tests/models/test_grammar_llama.py", "repo_id": "text-generation-inference", "token_count": 1346 }
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import pytest @pytest.fixture(scope="module") def t5_sharded_handle(launcher): with launcher("google/flan-t5-xxl", num_shard=4) as handle: yield handle @pytest.fixture(scope="module") async def t5_sharded(t5_sharded_handle): await t5_sharded_handle.health(300) return t5_sharded_handle.client @...
text-generation-inference/integration-tests/models/test_t5_sharded.py/0
{ "file_path": "text-generation-inference/integration-tests/models/test_t5_sharded.py", "repo_id": "text-generation-inference", "token_count": 443 }
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import argparse import datetime import json import os import traceback from typing import Dict, Tuple, List import GPUtil import docker from docker.models.containers import Container from loguru import logger import pandas as pd class InferenceEngineRunner: def __init__(self, model: str): self.model = mo...
text-generation-inference/load_tests/benchmarks.py/0
{ "file_path": "text-generation-inference/load_tests/benchmarks.py", "repo_id": "text-generation-inference", "token_count": 4444 }
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use crate::infer::Infer; use crate::server::{generate_internal, ComputeType}; use crate::{ChatRequest, ErrorResponse, GenerateParameters, GenerateRequest}; use axum::extract::Extension; use axum::http::{HeaderMap, StatusCode}; use axum::response::{IntoResponse, Response}; use axum::Json; use serde::{Deserialize, Serial...
text-generation-inference/router/src/vertex.rs/0
{ "file_path": "text-generation-inference/router/src/vertex.rs", "repo_id": "text-generation-inference", "token_count": 2983 }
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from setuptools import setup from torch.utils.cpp_extension import BuildExtension, CUDAExtension import torch extra_cuda_cflags = [] extra_cflags = [] if torch.version.hip: extra_cflags = ["-DLEGACY_HIPBLAS_DIRECT=ON"] extra_cuda_cflags = ["-DLEGACY_HIPBLAS_DIRECT=ON"] extra_compile_args = { "cxx": extra_...
text-generation-inference/server/exllama_kernels/setup.py/0
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#ifndef _qdq_8_cuh #define _qdq_8_cuh #include "qdq_util.cuh" #include "../../config.h" #if QMODE_8BIT == 1 // Not implemented #else __forceinline__ __device__ void shuffle_8bit_4 ( uint32_t* q, int stride ) { } __forceinline__ __device__ void dequant_8bit_8 ( const uint32_t q_0, const uint32_t ...
text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/quant/qdq_8.cuh/0
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import pytest from text_generation_server.pb import generate_pb2 from text_generation_server.models.causal_lm import CausalLMBatch, CausalLM @pytest.fixture(scope="session") def default_santacoder(): return CausalLM.fallback(model_id="bigcode/santacoder") @pytest.fixture def default_pb_request(default_pb_param...
text-generation-inference/server/tests/models/test_santacoder.py/0
{ "file_path": "text-generation-inference/server/tests/models/test_santacoder.py", "repo_id": "text-generation-inference", "token_count": 1480 }
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import torch import grpc from google.rpc import status_pb2, code_pb2 from grpc_status import rpc_status from grpc_interceptor.server import AsyncServerInterceptor from loguru import logger from typing import Callable, Any class ExceptionInterceptor(AsyncServerInterceptor): def __init__(self, shutdown_callback): ...
text-generation-inference/server/text_generation_server/interceptor.py/0
{ "file_path": "text-generation-inference/server/text_generation_server/interceptor.py", "repo_id": "text-generation-inference", "token_count": 545 }
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from typing import Any, Dict, List, Union from compressed_tensors import QuantizationConfig, QuantizationStatus from compressed_tensors.config import CompressionFormat from compressed_tensors.quantization import ( QuantizationScheme, QuantizationType, find_name_or_class_matches, ) from loguru import logger...
text-generation-inference/server/text_generation_server/layers/compressed_tensors/loader.py/0
{ "file_path": "text-generation-inference/server/text_generation_server/layers/compressed_tensors/loader.py", "repo_id": "text-generation-inference", "token_count": 3149 }
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# coding=utf-8 # Copyright 2025 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
text-generation-inference/server/text_generation_server/models/custom_modeling/gemma3/utils.py/0
{ "file_path": "text-generation-inference/server/text_generation_server/models/custom_modeling/gemma3/utils.py", "repo_id": "text-generation-inference", "token_count": 792 }
321
import torch from abc import ABC, abstractmethod from dataclasses import dataclass from typing import List, Optional from transformers import PreTrainedTokenizerBase from text_generation_server.pb import generate_pb2 from text_generation_server.pb.generate_pb2 import FinishReason class Batch(ABC): @abstractmet...
text-generation-inference/server/text_generation_server/models/types.py/0
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# coding=utf-8 # From: https://github.com/huggingface/peft/pull/1364 # Copyright 2024-present the HuggingFace Inc. team. # Modifications by Predibase, Inc. # # 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 th...
text-generation-inference/server/text_generation_server/utils/merges/utils.py/0
{ "file_path": "text-generation-inference/server/text_generation_server/utils/merges/utils.py", "repo_id": "text-generation-inference", "token_count": 1422 }
323
[target.aarch64-unknown-linux-musl] linker = "aarch64-linux-musl-gcc" rustflags = ["-C", "target-feature=-crt-static"]
tokenizers/bindings/node/.cargo/config.toml/0
{ "file_path": "tokenizers/bindings/node/.cargo/config.toml", "repo_id": "tokenizers", "token_count": 50 }
324
/* tslint:disable */ /* eslint-disable */ /* auto-generated by NAPI-RS */ export function bpeDecoder(suffix?: string | undefined | null): Decoder export function byteFallbackDecoder(): Decoder export function ctcDecoder( padToken?: string = '<pad>', wordDelimiterToken?: string | undefined | null, cleanup?: bool...
tokenizers/bindings/node/index.d.ts/0
{ "file_path": "tokenizers/bindings/node/index.d.ts", "repo_id": "tokenizers", "token_count": 2753 }
325
# `tokenizers-android-arm64` This is the **aarch64-linux-android** binary for `tokenizers`
tokenizers/bindings/node/npm/android-arm64/README.md/0
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# `tokenizers-linux-x64-musl` This is the **x86_64-unknown-linux-musl** binary for `tokenizers`
tokenizers/bindings/node/npm/linux-x64-musl/README.md/0
{ "file_path": "tokenizers/bindings/node/npm/linux-x64-musl/README.md", "repo_id": "tokenizers", "token_count": 38 }
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use crate::arc_rwlock_serde; use napi::bindgen_prelude::*; use napi_derive::napi; use serde::{Deserialize, Serialize}; use std::sync::{Arc, RwLock}; use tk::pre_tokenizers::PreTokenizerWrapper; use tk::PreTokenizedString; use tk::SplitDelimiterBehavior; use tokenizers as tk; #[napi(string_enum)] pub enum JsSplitDelimi...
tokenizers/bindings/node/src/pre_tokenizers.rs/0
{ "file_path": "tokenizers/bindings/node/src/pre_tokenizers.rs", "repo_id": "tokenizers", "token_count": 3151 }
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.PHONY: style check-style test DATA_DIR = data dir_guard=@mkdir -p $(@D) check_dirs := examples py_src/tokenizers tests # Format source code automatically style: python stub.py ruff check $(check_dirs) --fix ruff format $(check_dirs) # Check the source code is formatted correctly check-style: python stub.py -...
tokenizers/bindings/python/Makefile/0
{ "file_path": "tokenizers/bindings/python/Makefile", "repo_id": "tokenizers", "token_count": 349 }
329
from typing import Dict, Iterator, List, Optional, Union from tokenizers import AddedToken, Tokenizer, decoders, trainers from tokenizers.models import WordPiece from tokenizers.normalizers import BertNormalizer from tokenizers.pre_tokenizers import BertPreTokenizer from tokenizers.processors import BertProcessing fr...
tokenizers/bindings/python/py_src/tokenizers/implementations/bert_wordpiece.py/0
{ "file_path": "tokenizers/bindings/python/py_src/tokenizers/implementations/bert_wordpiece.py", "repo_id": "tokenizers", "token_count": 2637 }
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# Generated content DO NOT EDIT from .. import trainers Trainer = trainers.Trainer BpeTrainer = trainers.BpeTrainer UnigramTrainer = trainers.UnigramTrainer WordLevelTrainer = trainers.WordLevelTrainer WordPieceTrainer = trainers.WordPieceTrainer
tokenizers/bindings/python/py_src/tokenizers/trainers/__init__.py/0
{ "file_path": "tokenizers/bindings/python/py_src/tokenizers/trainers/__init__.py", "repo_id": "tokenizers", "token_count": 74 }
331
use pyo3::prelude::*; use tk::Token; #[pyclass(module = "tokenizers", name = "Token")] #[derive(Clone)] pub struct PyToken { token: Token, } impl From<Token> for PyToken { fn from(token: Token) -> Self { Self { token } } } impl From<PyToken> for Token { fn from(token: PyToken) -> Self { ...
tokenizers/bindings/python/src/token.rs/0
{ "file_path": "tokenizers/bindings/python/src/token.rs", "repo_id": "tokenizers", "token_count": 439 }
332
import pickle import pytest from tokenizers import NormalizedString from tokenizers.normalizers import ( BertNormalizer, Lowercase, Normalizer, Precompiled, Sequence, Strip, Prepend, Replace, ) class TestBertNormalizer: def test_instantiate(self): assert isinstance(BertNo...
tokenizers/bindings/python/tests/bindings/test_normalizers.py/0
{ "file_path": "tokenizers/bindings/python/tests/bindings/test_normalizers.py", "repo_id": "tokenizers", "token_count": 3243 }
333
import multiprocessing as mp import os import pytest import requests DATA_PATH = os.path.join("tests", "data") def download(url, with_filename=None): filename = with_filename if with_filename is not None else url.rsplit("/")[-1] filepath = os.path.join(DATA_PATH, filename) if not os.path.exists(filepa...
tokenizers/bindings/python/tests/utils.py/0
{ "file_path": "tokenizers/bindings/python/tests/utils.py", "repo_id": "tokenizers", "token_count": 1569 }
334
Documentation ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The node API has not been documented yet.
tokenizers/docs/source/api/node.inc/0
{ "file_path": "tokenizers/docs/source/api/node.inc", "repo_id": "tokenizers", "token_count": 22 }
335
[package] authors = ["Anthony MOI <m.anthony.moi@gmail.com>", "Nicolas Patry <patry.nicolas@protonmail.com>"] edition = "2018" name = "tokenizers" version = "0.21.4-dev.0" homepage = "https://github.com/huggingface/tokenizers" repository = "https://github.com/huggingface/tokenizers" documentation = "https://docs.rs/tok...
tokenizers/tokenizers/Cargo.toml/0
{ "file_path": "tokenizers/tokenizers/Cargo.toml", "repo_id": "tokenizers", "token_count": 993 }
336
mod utils; use tokenizers::models::bpe::{Vocab, BPE}; use tokenizers::Tokenizer; use wasm_bindgen::prelude::*; // When the `wee_alloc` feature is enabled, use `wee_alloc` as the global // allocator. #[cfg(feature = "wee_alloc")] #[global_allocator] static ALLOC: wee_alloc::WeeAlloc = wee_alloc::WeeAlloc::INIT; #[was...
tokenizers/tokenizers/examples/unstable_wasm/src/lib.rs/0
{ "file_path": "tokenizers/tokenizers/examples/unstable_wasm/src/lib.rs", "repo_id": "tokenizers", "token_count": 543 }
337
use crate::tokenizer::{Decoder, Result}; use serde::{Deserialize, Serialize}; #[derive(Deserialize, Clone, Debug, Serialize)] /// Allows decoding Original BPE by joining all the tokens and then replacing /// the suffix used to identify end-of-words by whitespaces #[serde(tag = "type")] #[non_exhaustive] pub struct BP...
tokenizers/tokenizers/src/decoders/bpe.rs/0
{ "file_path": "tokenizers/tokenizers/src/decoders/bpe.rs", "repo_id": "tokenizers", "token_count": 419 }
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//! [Unigram](https://arxiv.org/abs/1804.10959) model. mod lattice; mod model; mod serialization; mod trainer; mod trie; pub use lattice::*; pub use model::*; pub use trainer::*;
tokenizers/tokenizers/src/models/unigram/mod.rs/0
{ "file_path": "tokenizers/tokenizers/src/models/unigram/mod.rs", "repo_id": "tokenizers", "token_count": 72 }
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use crate::tokenizer::pattern::Pattern; use crate::tokenizer::Decoder; use crate::tokenizer::{NormalizedString, Normalizer, Result}; use crate::utils::SysRegex; use serde::{Deserialize, Serialize}; /// Represents the different patterns that `Replace` can use #[derive(Debug, Clone, PartialEq, Serialize, Deserialize, Eq...
tokenizers/tokenizers/src/normalizers/replace.rs/0
{ "file_path": "tokenizers/tokenizers/src/normalizers/replace.rs", "repo_id": "tokenizers", "token_count": 2049 }
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// Generated by modified Perl script at https://github.com/google/sentencepiece/blob/master/data/gen_unicode_scripts_code.pl // Unicode scripts : https://gist.github.com/Narsil/07556f26dc84a6baeff4d499e68d3cd2 // Rust adaptation : https://gist.github.com/Narsil/1df9fbbf5296a8d4d62de55dcb2fe700 #[derive(PartialEq, Debu...
tokenizers/tokenizers/src/pre_tokenizers/unicode_scripts/scripts.rs/0
{ "file_path": "tokenizers/tokenizers/src/pre_tokenizers/unicode_scripts/scripts.rs", "repo_id": "tokenizers", "token_count": 46440 }
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use crate::Result; use hf_hub::{api::sync::ApiBuilder, Repo, RepoType}; use std::collections::HashMap; use std::path::PathBuf; /// Defines the additional parameters available for the `from_pretrained` function #[derive(Debug, Clone)] pub struct FromPretrainedParameters { pub revision: String, pub user_agent: H...
tokenizers/tokenizers/src/utils/from_pretrained.rs/0
{ "file_path": "tokenizers/tokenizers/src/utils/from_pretrained.rs", "repo_id": "tokenizers", "token_count": 884 }
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#[cfg(not(debug_assertions))] use assert_approx_eq::assert_approx_eq; use std::collections::HashMap; use std::fs::read_to_string; use std::path::Path; #[cfg(not(debug_assertions))] use tokenizers::models::unigram::Lattice; use tokenizers::models::unigram::Unigram; use tokenizers::models::unigram::UnigramTrainer; use to...
tokenizers/tokenizers/tests/unigram.rs/0
{ "file_path": "tokenizers/tokenizers/tests/unigram.rs", "repo_id": "tokenizers", "token_count": 1697 }
343
{ "source": { "excludePattern": "" } }
transformers.js/docs/jsdoc-conf.json/0
{ "file_path": "transformers.js/docs/jsdoc-conf.json", "repo_id": "transformers.js", "token_count": 30 }
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# Running models on WebGPU WebGPU is a new web standard for accelerated graphics and compute. The [API](https://developer.mozilla.org/en-US/docs/Web/API/WebGPU_API) enables web developers to use the underlying system's GPU to carry out high-performance computations directly in the browser. WebGPU is the successor to [...
transformers.js/docs/source/guides/webgpu.md/0
{ "file_path": "transformers.js/docs/source/guides/webgpu.md", "repo_id": "transformers.js", "token_count": 1452 }
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function formatBytes(bytes, decimals = 0) { const sizes = ["Bytes", "KB", "MB", "GB", "TB"]; if (bytes === 0) return "0 Bytes"; const i = parseInt(Math.floor(Math.log(bytes) / Math.log(1000)), 10); const rounded = (bytes / Math.pow(1000, i)).toFixed(decimals); return rounded + " " + sizes[i]; } exp...
transformers.js/examples/code-completion/src/components/Progress.jsx/0
{ "file_path": "transformers.js/examples/code-completion/src/components/Progress.jsx", "repo_id": "transformers.js", "token_count": 278 }
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import { env, AutoTokenizer, AutoModelForSequenceClassification } from '@xenova/transformers'; // Skip local model check since we are downloading the model from the Hugging Face Hub. env.allowLocalModels = false; class CrossEncoderSingleton { static model_id = 'mixedbread-ai/mxbai-rerank-xsmall-v1'; static mo...
transformers.js/examples/cross-encoder/src/worker.js/0
{ "file_path": "transformers.js/examples/cross-encoder/src/worker.js", "repo_id": "transformers.js", "token_count": 786 }
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// Adapted from https://www.npmjs.com/package/audiobuffer-to-wav export function encodeWAV(samples, sampleRate = 16000) { let offset = 44; const buffer = new ArrayBuffer(offset + samples.length * 4); const view = new DataView(buffer); /* RIFF identifier */ writeString(view, 0, 'RIFF') /* RIFF ...
transformers.js/examples/musicgen-web/src/utils.js/0
{ "file_path": "transformers.js/examples/musicgen-web/src/utils.js", "repo_id": "transformers.js", "token_count": 787 }
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'use client' import { useState, useEffect, useRef, useCallback } from 'react' export default function Home() { // Keep track of the classification result and the model loading status. const [result, setResult] = useState(null); const [ready, setReady] = useState(null); // Create a reference to the worker ob...
transformers.js/examples/next-client/src/app/page.js/0
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import { useEffect, useRef, useState } from 'react' import LanguageSelector from './components/LanguageSelector'; import Progress from './components/Progress'; import './App.css' function App() { // Model loading const [ready, setReady] = useState(null); const [disabled, setDisabled] = useState(false); const...
transformers.js/examples/react-translator/src/App.jsx/0
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<!DOCTYPE html> <html lang="en"> <head> <meta charset="UTF-8" /> <link rel="stylesheet" href="index.css" /> <meta name="viewport" content="width=device-width, initial-scale=1.0" /> <title>Transformers.js - Segment Anything WebGPU</title> </head> <body> <h1>Segment Anything WebGPU</h1> <h3>In-...
transformers.js/examples/segment-anything-client/index.html/0
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{ "compilerOptions": { "paths": { "@/*": ["./src/*"] } } }
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/** @type {import('tailwindcss').Config} */ module.exports = { content: [ './src/pages/**/*.{js,ts,jsx,tsx,mdx}', './src/components/**/*.{js,ts,jsx,tsx,mdx}', './src/app/**/*.{js,ts,jsx,tsx,mdx}', ], theme: { extend: { boxShadow: { highlight: 'inset 0 0 0 1px rgba(255, 255, 255, 0.1)...
transformers.js/examples/semantic-image-search-client/tailwind.config.js/0
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import { downloadImage } from '../utils.js' import Image from 'next/image' export function Modal({ currentImage, setCurrentImage }) { return ( <div className='fixed inset-0 z-30 backdrop-blur-2xl w-full h-full bg-black top-0 left-0 transition' style={{ backgroundColo...
transformers.js/examples/semantic-image-search/src/app/components/Modal.jsx/0
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import { useEffect, useRef } from "react"; export default function AudioPlayer({ audioUrl, mimeType }) { const audioPlayer = useRef(null); const audioSource = useRef(null); // Updates src when url changes useEffect(() => { if (audioPlayer.current && audioSource.current) { audioSour...
transformers.js/examples/text-to-speech-client/src/components/AudioPlayer.jsx/0
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#root { max-width: 1280px; width: 100%; margin: 0 auto; padding: 2rem; text-align: center; display: flex; justify-content: center; align-items: center; flex-direction: column; }
transformers.js/examples/tokenizer-playground/src/App.css/0
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export default function UserIcon(props) { return ( <svg {...props} xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" strokeWidth="2" strok...
transformers.js/examples/webgpu-vlm/src/components/icons/UserIcon.jsx/0
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def generate_tokenizer_json(tokenizer): vocab = tokenizer.vocab special_tokens_vocab = vocab if "<pad>" not in tokenizer.vocab: # For MMS tokenizers, the vocab is of the form: # { # language_id: { language_vocab } # } # So, to get the list of special tokens, we ju...
transformers.js/scripts/extra/wav2vec2.py/0
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/** * @module generation/stopping_criteria */ import { Callable } from "../utils/generic.js"; // NOTE: // Stopping Criteria returns a list of `batch_size` booleans, indicating whether each sequence in the batch should be stopped. /** * Abstract base class for all stopping criteria that can be applied during gene...
transformers.js/src/generation/stopping_criteria.js/0
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import { ImageProcessor, } from "../../base/image_processors_utils.js"; export class DINOv3ViTImageProcessor extends ImageProcessor { }
transformers.js/src/models/dinov3_vit/image_processing_dinov3_vit.js/0
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import { Processor } from "../../base/processing_utils.js"; import { AutoImageProcessor } from "../auto/image_processing_auto.js"; import { AutoTokenizer } from "../../tokenizers.js"; import { mergeArrays } from "../../utils/core.js"; import { Tensor } from "../../utils/tensor.js"; import { RawImage } from "../../util...
transformers.js/src/models/janus/processing_janus.js/0
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import { OwlViTImageProcessor } from "../owlvit/image_processing_owlvit.js"; // NOTE: extends OwlViTImageProcessor export class Owlv2ImageProcessor extends OwlViTImageProcessor { }
transformers.js/src/models/owlv2/image_processing_owlv2.js/0
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import { FeatureExtractor, validate_audio_inputs } from '../../base/feature_extraction_utils.js'; import { Tensor } from '../../utils/tensor.js'; import { mel_filter_bank, spectrogram, window_function } from '../../utils/audio.js'; export class SeamlessM4TFeatureExtractor extends FeatureExtractor { constructor(co...
transformers.js/src/models/seamless_m4t/feature_extraction_seamless_m4t.js/0
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/// <reference types="@webgpu/types" /> import { apis } from "../env.js"; import { DEVICE_TYPES } from "./devices.js"; // TODO: Use the adapter from `env.backends.onnx.webgpu.adapter` to check for `shader-f16` support, // when available in https://github.com/microsoft/onnxruntime/pull/19940. // For more information,...
transformers.js/src/utils/dtypes.js/0
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import { AutoFeatureExtractor, ASTFeatureExtractor } from "../../../src/transformers.js"; import { load_cached_audio } from "../../asset_cache.js"; import { MAX_FEATURE_EXTRACTOR_LOAD_TIME, MAX_TEST_EXECUTION_TIME } from "../../init.js"; export default () => { // ASTFeatureExtractor describe("ASTFeatureExtractor"...
transformers.js/tests/models/audio_spectrogram_transformer/test_feature_extraction_audio_spectrogram_transformer.js/0
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import { GPT2Tokenizer, GPT2LMHeadModel } 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("GPT2LMHeadModel", () => { const model_id = "hf-internal-testing/tiny-random...
transformers.js/tests/models/gpt2/test_modeling_gpt2.js/0
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import { PreTrainedTokenizer, Lfm2ForCausalLM } 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("Lfm2ForCausalLM", () => { const model_id = "onnx-internal-testing/tin...
transformers.js/tests/models/lfm2/test_modeling_lfm2.js/0
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import { NllbTokenizer } from "../../../src/tokenizers.js"; import { BASE_TEST_STRINGS } from "../test_strings.js"; export const TOKENIZER_CLASS = NllbTokenizer; export const TEST_CONFIG = { "Xenova/nllb-200-distilled-600M": { SIMPLE: { text: BASE_TEST_STRINGS.SIMPLE, tokens: ["\u2581How", "\u2581are...
transformers.js/tests/models/nllb/test_tokenization_nllb.js/0
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import { AutoProcessor, Qwen2VLProcessor } 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("Qwen2VLProcessor", () => { const model_id = "hf-internal-te...
transformers.js/tests/models/qwen2_vl/test_processor_qwen2_vl.js/0
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import { AutoFeatureExtractor, WhisperFeatureExtractor } from "../../../src/transformers.js"; import { load_cached_audio } from "../../asset_cache.js"; import { MAX_FEATURE_EXTRACTOR_LOAD_TIME, MAX_TEST_EXECUTION_TIME } from "../../init.js"; export default () => { // WhisperFeatureExtractor describe("WhisperFeatu...
transformers.js/tests/models/whisper/test_feature_extraction_whisper.js/0
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import { pipeline, ImageToImagePipeline } from "../../src/transformers.js"; import { MAX_MODEL_LOAD_TIME, MAX_TEST_EXECUTION_TIME, MAX_MODEL_DISPOSE_TIME, DEFAULT_MODEL_OPTIONS } from "../init.js"; import { load_cached_image } from "../asset_cache.js"; const PIPELINE_ID = "image-to-image"; export default () => { d...
transformers.js/tests/pipelines/test_pipelines_image_to_image.js/0
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import fs from "node:fs"; import path from "node:path"; import { fileURLToPath } from "node:url"; export async function loadAudio(url) { // NOTE: Since the Web Audio API is not available in Node.js, we will need to use the `wavefile` library to obtain the raw audio data. // For more information, see: https://huggi...
transformers.js/tests/test_utils.js/0
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import re import argparse def parse_pytest_output(file_path): skipped_tests = {} skipped_count = 0 with open(file_path, 'r') as file: for line in file: match = re.match(r'^SKIPPED \[(\d+)\] (tests/.*): (.*)$', line) if match: skipped_count += 1 ...
transformers/.circleci/parse_test_outputs.py/0
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.PHONY: deps_table_update modified_only_fixup extra_style_checks quality style fixup fix-copies test test-examples benchmark # make sure to test the local checkout in scripts and not the pre-installed one (don't use quotes!) export PYTHONPATH = src check_dirs := examples tests src utils exclude_folders := "" modif...
transformers/Makefile/0
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FROM nvidia/cuda:12.6.0-cudnn-devel-ubuntu22.04 LABEL maintainer="Hugging Face" ARG DEBIAN_FRONTEND=noninteractive # Use login shell to read variables from `~/.profile` (to pass dynamic created variables between RUN commands) SHELL ["sh", "-lc"] # The following `ARG` are mainly used to specify the versions explicitl...
transformers/docker/transformers-all-latest-gpu/Dockerfile/0
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<!--- Copyright 2020 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or ...
transformers/docs/README.md/0
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# قاموس المصطلحات يحدد هذا المسرد مصطلحات التعلم الآلي العامة و 🤗 Transformers لمساعدتك على فهم الوثائق بشكل أفضل. ## A ### قناع الانتباه (Attention Mask) قناع الانتباه هو مُدخل اختياري يستخدم عند تجميع التسلسلات معًا <Youtube id="M6adb1j2jPI"/> يشير هذا المُدخل إلى النموذج أى الرموز المميزة (tokens) التي يجب ال...
transformers/docs/source/ar/glossary.md/0
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# خطوط الأنابيب الاستدلال يجعل [`pipeline`] من السهل استخدام أي نموذج من [Hub](https://huggingface.co/models) للاستدلال لأي مهام خاصة باللغة أو الرؤية الحاسوبية أو الكلام أو المهام متعددة الوسائط. حتى إذا لم يكن لديك خبرة في طريقة معينة أو لم تكن على دراية بالرمز الأساسي وراء النماذج، يمكنك مع ذلك استخدامها للاستدلال ...
transformers/docs/source/ar/pipeline_tutorial.md/0
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# كيف تُنجز نماذج 🤗 Transformers المهام؟ في [ما الذي يمكن أن تفعله نماذج 🤗 Transformers](task_summary)، تعلمت عن معالجة اللغات الطبيعية (NLP)، والخطاب والصوت، ورؤية الحاسب، وبعض تطبيقاتها المهمة. ستلقي هذه الصفحة نظرة فاحصة على كيفية حل النماذج لهذه المهام وتوضيح ما يحدث ما يحدث وراء الكواليس. هناك العديد من الطرق ...
transformers/docs/source/ar/tasks_explained.md/0
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<!--- Copyright 2022 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or ...
transformers/docs/source/de/installation.md/0
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<!--Copyright 2024 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/en/add_new_model.md/0
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<!--Copyright 2024 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/en/debugging.md/0
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<!--Copyright 2021 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/en/internal/file_utils.md/0
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<!--Copyright 2020 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/en/main_classes/callback.md/0
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<!--Copyright 2023 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/en/main_classes/quantization.md/0
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<!--Copyright 2023 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/en/model_doc/bark.md/0
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<!--Copyright 2024 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/en/model_doc/dab-detr.md/0
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<!--Copyright 2024 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/en/model_doc/depth_pro.md/0
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<!--Copyright 2023 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/en/model_doc/falcon.md/0
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<!--Copyright 2024 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agree...
transformers/docs/source/en/model_doc/gemma2.md/0
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<!--Copyright 2022 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/en/model_doc/gpt_neox_japanese.md/0
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<!--Copyright 2024 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/en/model_doc/hiera.md/0
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<!--Copyright 2024 JetMoe team and The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicab...
transformers/docs/source/en/model_doc/jetmoe.md/0
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<!--Copyright 2024 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/en/model_doc/llama3.md/0
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<!--Copyright 2022 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/en/model_doc/mask2former.md/0
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<!--Copyright 2024 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/en/model_doc/mllama.md/0
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<!--Copyright 2020 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/en/model_doc/mt5.md/0
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<!--Copyright 2024 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
transformers/docs/source/en/model_doc/phi3.md/0
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<!--Copyright 2025 The Qwen Team and The HuggingFace Inc. team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by a...
transformers/docs/source/en/model_doc/qwen2_5_vl.md/0
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