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""" Tensorflow Preprocessing Adapter Allows use of Tensorflow preprocessing pipeline in PyTorch Transform Copyright of original Tensorflow code below. Hacked together by / Copyright 2020 Ross Wightman """ # Copyright 2018 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2....
pytorch-image-models/timm/data/tf_preprocessing.py/0
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""" Conv2d w/ Same Padding Hacked together by / Copyright 2020 Ross Wightman """ import torch import torch.nn as nn import torch.nn.functional as F from typing import Tuple, Optional from .config import is_exportable, is_scriptable from .padding import pad_same, pad_same_arg, get_padding_value _USE_EXPORT_CONV = Fa...
pytorch-image-models/timm/layers/conv2d_same.py/0
{ "file_path": "pytorch-image-models/timm/layers/conv2d_same.py", "repo_id": "pytorch-image-models", "token_count": 1560 }
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""" Global Response Normalization Module Based on the GRN layer presented in `ConvNeXt-V2 - Co-designing and Scaling ConvNets with Masked Autoencoders` - https://arxiv.org/abs/2301.00808 This implementation * works for both NCHW and NHWC tensor layouts * uses affine param names matching existing torch norm layers * s...
pytorch-image-models/timm/layers/grn.py/0
{ "file_path": "pytorch-image-models/timm/layers/grn.py", "repo_id": "pytorch-image-models", "token_count": 565 }
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""" Padding Helpers Hacked together by / Copyright 2020 Ross Wightman """ import math from typing import List, Tuple, Union import torch import torch.nn.functional as F from .helpers import to_2tuple # Calculate symmetric padding for a convolution def get_padding(kernel_size: int, stride: int = 1, dilation: int = ...
pytorch-image-models/timm/layers/padding.py/0
{ "file_path": "pytorch-image-models/timm/layers/padding.py", "repo_id": "pytorch-image-models", "token_count": 1439 }
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from typing import Callable, Tuple, Type, Union import torch LayerType = Union[str, Callable, Type[torch.nn.Module]] PadType = Union[str, int, Tuple[int, int]]
pytorch-image-models/timm/layers/typing.py/0
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import collections.abc import math import re from collections import defaultdict from itertools import chain from typing import Any, Callable, Dict, Iterator, Tuple, Type, Union import torch from torch import nn as nn from torch.utils.checkpoint import checkpoint __all__ = ['model_parameters', 'named_apply', 'named_m...
pytorch-image-models/timm/models/_manipulate.py/0
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""" ConvNeXt Papers: * `A ConvNet for the 2020s` - https://arxiv.org/pdf/2201.03545.pdf @Article{liu2022convnet, author = {Zhuang Liu and Hanzi Mao and Chao-Yuan Wu and Christoph Feichtenhofer and Trevor Darrell and Saining Xie}, title = {A ConvNet for the 2020s}, journal = {Proceedings of the IEEE/CVF Confer...
pytorch-image-models/timm/models/convnext.py/0
{ "file_path": "pytorch-image-models/timm/models/convnext.py", "repo_id": "pytorch-image-models", "token_count": 25705 }
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# FastViT for PyTorch # # Original implementation and weights from https://github.com/apple/ml-fastvit # # For licensing see accompanying LICENSE file at https://github.com/apple/ml-fastvit/tree/main # Original work is copyright (C) 2023 Apple Inc. All Rights Reserved. # import os from functools import partial from typ...
pytorch-image-models/timm/models/fastvit.py/0
{ "file_path": "pytorch-image-models/timm/models/fastvit.py", "repo_id": "pytorch-image-models", "token_count": 29316 }
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""" Pytorch Inception-V4 implementation Sourced from https://github.com/Cadene/tensorflow-model-zoo.torch (MIT License) which is based upon Google's Tensorflow implementation and pretrained weights (Apache 2.0 License) """ from functools import partial import torch import torch.nn as nn from timm.data import IMAGENET...
pytorch-image-models/timm/models/inception_v4.py/0
{ "file_path": "pytorch-image-models/timm/models/inception_v4.py", "repo_id": "pytorch-image-models", "token_count": 5547 }
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""" RDNet Copyright (c) 2024-present NAVER Cloud Corp. Apache-2.0 """ from functools import partial from typing import List, Optional, Tuple, Union, Callable import torch import torch.nn as nn from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD from timm.layers import DropPath, NormMlpClassifierHead, C...
pytorch-image-models/timm/models/rdnet.py/0
{ "file_path": "pytorch-image-models/timm/models/rdnet.py", "repo_id": "pytorch-image-models", "token_count": 9321 }
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""" Swin Transformer V2 A PyTorch impl of : `Swin Transformer V2: Scaling Up Capacity and Resolution` - https://arxiv.org/pdf/2111.09883 Code adapted from https://github.com/ChristophReich1996/Swin-Transformer-V2, original copyright/license info below This implementation is experimental and subject to change in ...
pytorch-image-models/timm/models/swin_transformer_v2_cr.py/0
{ "file_path": "pytorch-image-models/timm/models/swin_transformer_v2_cr.py", "repo_id": "pytorch-image-models", "token_count": 21270 }
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""" Cross-Covariance Image Transformer (XCiT) in PyTorch Paper: - https://arxiv.org/abs/2106.09681 Same as the official implementation, with some minor adaptations, original copyright below - https://github.com/facebookresearch/xcit/blob/master/xcit.py Modifications and additions for timm hacked together by ...
pytorch-image-models/timm/models/xcit.py/0
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""" Optimizer Factory w/ Custom Weight Decay Hacked together by / Copyright 2021 Ross Wightman """ import logging from itertools import islice from typing import Optional, Callable, Tuple import torch import torch.nn as nn import torch.optim as optim from timm.models import group_parameters from .adabelief import Ad...
pytorch-image-models/timm/optim/optim_factory.py/0
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import fnmatch import re from collections import OrderedDict from typing import Union, Optional, List import torch class AttentionExtract(torch.nn.Module): # defaults should cover a significant number of timm models with attention maps. default_node_names = ['*attn.softmax'] default_module_names = ['*att...
pytorch-image-models/timm/utils/attention_extract.py/0
{ "file_path": "pytorch-image-models/timm/utils/attention_extract.py", "repo_id": "pytorch-image-models", "token_count": 1467 }
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#!/usr/bin/env python3 """ ImageNet Training Script This is intended to be a lean and easily modifiable ImageNet training script that reproduces ImageNet training results with some of the latest networks and training techniques. It favours canonical PyTorch and standard Python style over trying to be able to 'do it al...
pytorch-image-models/train.py/0
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# Text Generation Inference - TensorRT-LLM Backend Implementation ## Description This folder provides the sources of the TensorRT-LLM backend implementation powered by TensorRT-LLM Executor new API ## Simplified Request Sequence ```mermaid sequenceDiagram actor User participant TextGenerationInference.HttpS...
text-generation-inference/backends/trtllm/README.md/0
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use clap::Parser; use std::collections::HashMap; use std::path::PathBuf; use text_generation_backends_trtllm::errors::TensorRtLlmBackendError; use text_generation_backends_trtllm::TensorRtLlmBackend; use text_generation_router::server; use tokenizers::{FromPretrainedParameters, Tokenizer}; /// App Configuration #[deri...
text-generation-inference/backends/trtllm/src/main.rs/0
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/// Inspired by https://github.com/hatoo/oha/blob/bb989ea3cd77727e7743e7daa60a19894bb5e901/src/monitor.rs use crate::generation::{Decode, Message, Prefill}; use crossterm::event::{KeyCode, KeyEvent, KeyModifiers}; use text_generation_client::ClientError; use tokio::sync::mpsc; use tui::backend::Backend; use tui::layout...
text-generation-inference/benchmark/src/app.rs/0
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import pytest from text_generation.types import Parameters, Request from text_generation.errors import ValidationError def test_parameters_validation(): # Test best_of Parameters(best_of=1) with pytest.raises(ValidationError): Parameters(best_of=0) with pytest.raises(ValidationError): ...
text-generation-inference/clients/python/tests/test_types.py/0
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# Model safety. [Pytorch uses pickle](https://pytorch.org/docs/master/generated/torch.load.html) by default meaning that for quite a long while *Every* model using that format is potentially executing unintended code while purely loading the model. There is a big red warning on Python's page for pickle [link](https:/...
text-generation-inference/docs/source/basic_tutorials/safety.md/0
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# Using TGI with AMD GPUs TGI is supported and tested on [AMD Instinct MI210](https://www.amd.com/en/products/accelerators/instinct/mi200/mi210.html), [MI250](https://www.amd.com/en/products/accelerators/instinct/mi200/mi250.html) and [MI300](https://www.amd.com/en/products/accelerators/instinct/mi300.html) GPUs. The ...
text-generation-inference/docs/source/installation_amd.md/0
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{ "details": { "best_of_sequences": null, "finish_reason": "length", "generated_tokens": 10, "prefill": [ { "id": 17934, "logprob": null, "text": "Pour" }, { "id": 49833, "logprob": -10.5703125, "text": " dég" }, { "...
text-generation-inference/integration-tests/models/__snapshots__/test_bloom_560m/test_bloom_560m.json/0
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221
[ { "details": { "best_of_sequences": null, "finish_reason": "length", "generated_tokens": 10, "prefill": [ { "id": 100000, "logprob": null, "text": "<|begin▁of▁sentence|>" }, { "id": 3533, "logprob": -9.625, ...
text-generation-inference/integration-tests/models/__snapshots__/test_flash_deepseek_v2/test_flash_deepseek_v2_load.json/0
{ "file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_deepseek_v2/test_flash_deepseek_v2_load.json", "repo_id": "text-generation-inference", "token_count": 4940 }
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[ { "details": { "best_of_sequences": null, "finish_reason": "length", "generated_tokens": 10, "prefill": [ { "id": 1, "logprob": null, "text": "<s>" }, { "id": 1024, "logprob": -10.578125, "text": "name" ...
text-generation-inference/integration-tests/models/__snapshots__/test_flash_grammar_llama/test_flash_llama_grammar_load.json/0
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{ "details": { "best_of_sequences": null, "finish_reason": "length", "generated_tokens": 10, "prefill": [ { "id": 1, "logprob": null, "text": "<s>" }, { "id": 4321, "logprob": -12.390625, "text": "Test" }, { "id": 20...
text-generation-inference/integration-tests/models/__snapshots__/test_flash_llama_marlin/test_flash_llama_marlin_all_params.json/0
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{ "details": { "best_of_sequences": null, "finish_reason": "eos_token", "generated_tokens": 8, "prefill": [], "seed": null, "tokens": [ { "id": 2502, "logprob": -1.7890625, "special": false, "text": "image" }, { "id": 2196, "log...
text-generation-inference/integration-tests/models/__snapshots__/test_flash_pali_gemma/test_flash_pali_gemma_two_images.json/0
{ "file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_pali_gemma/test_flash_pali_gemma_two_images.json", "repo_id": "text-generation-inference", "token_count": 719 }
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{ "details": { "finish_reason": "length", "generated_tokens": 40, "prefill": [], "seed": null, "tokens": [ { "id": 13, "logprob": -1.0488281, "special": false, "text": "\n" }, { "id": 13, "logprob": -1.0800781, "special": fa...
text-generation-inference/integration-tests/models/__snapshots__/test_lora_mistral/test_lora_mistral_without_adapter.json/0
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import pytest @pytest.fixture(scope="module") def flash_gemma_handle(launcher): with launcher("google/gemma-2b", num_shard=1) as handle: yield handle @pytest.fixture(scope="module") async def flash_gemma(flash_gemma_handle): await flash_gemma_handle.health(300) return flash_gemma_handle.client ...
text-generation-inference/integration-tests/models/test_flash_gemma.py/0
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import pytest @pytest.fixture(scope="module") def flash_phi_handle(launcher): with launcher("microsoft/phi-2", num_shard=1) as handle: yield handle @pytest.fixture(scope="module") async def flash_phi(flash_phi_handle): await flash_phi_handle.health(300) return flash_phi_handle.client @pytest.m...
text-generation-inference/integration-tests/models/test_flash_phi.py/0
{ "file_path": "text-generation-inference/integration-tests/models/test_flash_phi.py", "repo_id": "text-generation-inference", "token_count": 749 }
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import pytest @pytest.fixture(scope="module") def neox_sharded_handle(launcher): with launcher( "OpenAssistant/oasst-sft-1-pythia-12b", num_shard=2, use_flash_attention=False ) as handle: yield handle @pytest.fixture(scope="module") async def neox_sharded(neox_sharded_handle): await neox...
text-generation-inference/integration-tests/models/test_neox_sharded.py/0
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{ pkgs, nix-filter }: let filter = nix-filter.lib; in with pkgs; defaultCrateOverrides // { aws-lc-rs = attrs: { # aws-lc-rs does its own custom parsing of Cargo environment # variables like DEP_.*_INCLUDE. However buildRustCrate does # not use the version number, so the parsing fails. postPatch = ...
text-generation-inference/nix/crate-overrides.nix/0
{ "file_path": "text-generation-inference/nix/crate-overrides.nix", "repo_id": "text-generation-inference", "token_count": 908 }
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use opentelemetry::sdk::propagation::TraceContextPropagator; use opentelemetry::sdk::trace; use opentelemetry::sdk::trace::Sampler; use opentelemetry::sdk::Resource; use opentelemetry::{global, KeyValue}; use opentelemetry_otlp::WithExportConfig; use tracing_subscriber::layer::SubscriberExt; use tracing_subscriber::uti...
text-generation-inference/router/src/logging.rs/0
{ "file_path": "text-generation-inference/router/src/logging.rs", "repo_id": "text-generation-inference", "token_count": 1445 }
231
lorax_punica_commit := c71861a653412267dc27ec86013dd945ce3474bc build-lorax-punica: if [ ! -d 'lorax-punica' ]; then \ git clone --no-checkout https://github.com/predibase/lorax.git lorax-punica; \ fi cd lorax-punica && git sparse-checkout set server/punica_kernels && git checkout $(lorax_punica_commit) cd lorax...
text-generation-inference/server/Makefile-lorax-punica/0
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// Adapted from turboderp exllama: https://github.com/turboderp/exllama #include <torch/extension.h> #include <c10/cuda/CUDAGuard.h> #include <ATen/cuda/CUDAContext.h> #include <cuda_runtime.h> #include <cuda_fp16.h> #include <cstdint> #include <cstdio> #include "util.cuh" #include "tuning.h" #include "cuda_buffers.cu...
text-generation-inference/server/exllama_kernels/exllama_kernels/exllama_ext.cpp/0
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#ifndef _qdq_2_cuh #define _qdq_2_cuh #include "qdq_util.cuh" #include "../../config.h" #if QMODE_2BIT == 1 // Permutation: // // ffddbb99 77553311 eeccaa88 66442200 __forceinline__ __device__ void shuffle_2bit_16 ( uint32_t* q, int stride ) { uint32_t qa = q[0]; uint32_t qb = 0; #pragma unrol...
text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/quant/qdq_2.cuh/0
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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 CausalLMBatch from text_generation_server.utils import weight_hub_files, download_weights from text_generation_server.models.bl...
text-generation-inference/server/tests/models/test_bloom.py/0
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# Origin: https://github.com/predibase/lorax # Path: lorax/server/lorax_server/adapters/weights.py # License: Apache License Version 2.0, January 2004 from abc import ABC, abstractclassmethod from collections import defaultdict from dataclasses import dataclass from typing import Dict, List, Optional, Set, Type...
text-generation-inference/server/text_generation_server/adapters/weights.py/0
{ "file_path": "text-generation-inference/server/text_generation_server/adapters/weights.py", "repo_id": "text-generation-inference", "token_count": 1824 }
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from dataclasses import dataclass import torch from EETQ import quant_weights, w8_a16_gemm from text_generation_server.utils.weights import UnquantizedWeight @dataclass class EETQWeight(UnquantizedWeight): weight: torch.Tensor def get_linear(self, bias: torch.Tensor): try: from text_gene...
text-generation-inference/server/text_generation_server/layers/eetq.py/0
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from dataclasses import dataclass from typing import List, Optional, Union import torch import torch.nn as nn from text_generation_server.layers.marlin.util import _check_marlin_kernels from text_generation_server.utils.weights import Weight, Weights, WeightsLoader try: import marlin_kernels except ImportError: ...
text-generation-inference/server/text_generation_server/layers/marlin/marlin.py/0
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# coding=utf-8 # Copyright 2022 EleutherAI and the HuggingFace Inc. team. All rights reserved. # # This code is based on EleutherAI's GPT-NeoX library and the GPT-NeoX # and OPT implementations in this library. It has been modified from its # original forms to accommodate minor architectural differences compared # to G...
text-generation-inference/server/text_generation_server/models/custom_modeling/flash_gemma2_modeling.py/0
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import torch import os from loguru import logger from typing import Dict, Optional from text_generation_server.utils.log import log_master PREFIX_CACHING = os.getenv("USE_PREFIX_CACHING").lower() in {"1", "true"} log_master(logger.info, f"Using prefix caching = {PREFIX_CACHING}") ATTENTION = os.getenv("ATTENTION") _e...
text-generation-inference/server/text_generation_server/models/globals.py/0
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import os import torch from datetime import timedelta from loguru import logger from text_generation_server.utils.import_utils import SYSTEM # Tensor Parallelism settings RANK = int(os.getenv("RANK", "0")) WORLD_SIZE = int(os.getenv("WORLD_SIZE", "1")) # CUDA memory fraction MEMORY_FRACTION = float(os.getenv("CUDA_M...
text-generation-inference/server/text_generation_server/utils/dist.py/0
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import subprocess import argparse import ast import json import os TEMPLATE = """ # Supported Models and Hardware Text Generation Inference enables serving optimized models on specific hardware for the highest performance. The following sections list which models (VLMs & LLMs) are supported. ## Supported Models SUP...
text-generation-inference/update_doc.py/0
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extern crate napi_build; fn main() { napi_build::setup(); }
tokenizers/bindings/node/build.rs/0
{ "file_path": "tokenizers/bindings/node/build.rs", "repo_id": "tokenizers", "token_count": 26 }
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// import { promisify } from 'util' import { BPE, Tokenizer, mergeEncodings, slice } from '../../' describe('slice', () => { const text = 'My name is John 👋' const sliceText = slice.bind({}, text) it('returns the full text when no params', () => { const sliced = sliceText() expect(sliced).toEqual(text...
tokenizers/bindings/node/lib/bindings/utils.test.ts/0
{ "file_path": "tokenizers/bindings/node/lib/bindings/utils.test.ts", "repo_id": "tokenizers", "token_count": 1866 }
244
{ "name": "tokenizers-linux-arm64-musl", "version": "0.13.4-rc1", "os": [ "linux" ], "cpu": [ "arm64" ], "main": "tokenizers.linux-arm64-musl.node", "files": [ "tokenizers.linux-arm64-musl.node" ], "description": "Tokenizers platform specific bindings", "keywords": [ "napi-rs", ...
tokenizers/bindings/node/npm/linux-arm64-musl/package.json/0
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#![deny(clippy::all)] pub const VERSION: &str = env!("CARGO_PKG_VERSION"); mod arc_rwlock_serde; pub mod decoders; pub mod encoding; pub mod models; pub mod normalizers; pub mod pre_tokenizers; pub mod processors; pub mod tasks; pub mod tokenizer; pub mod trainers; pub mod utils;
tokenizers/bindings/node/src/lib.rs/0
{ "file_path": "tokenizers/bindings/node/src/lib.rs", "repo_id": "tokenizers", "token_count": 102 }
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# Changelog All notable changes to this project will be documented in this file. The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/), and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html). ## [0.13.2] - [#1096] Python 3.11 support ## [0.13.1] - [#1072]...
tokenizers/bindings/python/CHANGELOG.md/0
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# Generated content DO NOT EDIT class Decoder: """ Base class for all decoders This class is not supposed to be instantiated directly. Instead, any implementation of a Decoder will return an instance of this class when instantiated. """ def decode(self, tokens): """ Decode the g...
tokenizers/bindings/python/py_src/tokenizers/decoders/__init__.pyi/0
{ "file_path": "tokenizers/bindings/python/py_src/tokenizers/decoders/__init__.pyi", "repo_id": "tokenizers", "token_count": 3184 }
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from .visualizer import Annotation, EncodingVisualizer
tokenizers/bindings/python/py_src/tokenizers/tools/__init__.py/0
{ "file_path": "tokenizers/bindings/python/py_src/tokenizers/tools/__init__.py", "repo_id": "tokenizers", "token_count": 13 }
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use pyo3::types::*; use pyo3::{exceptions, prelude::*}; use std::sync::{Arc, RwLock}; use crate::error::ToPyResult; use crate::utils::{PyNormalizedString, PyNormalizedStringRefMut, PyPattern}; use serde::ser::SerializeStruct; use serde::{Deserialize, Deserializer, Serialize, Serializer}; use tk::normalizers::{ Ber...
tokenizers/bindings/python/src/normalizers.rs/0
{ "file_path": "tokenizers/bindings/python/src/normalizers.rs", "repo_id": "tokenizers", "token_count": 11989 }
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import json import pickle import pytest from tokenizers.decoders import ( CTC, BPEDecoder, ByteLevel, Decoder, Metaspace, Sequence, WordPiece, ByteFallback, Replace, Strip, Fuse, ) class TestByteLevel: def test_instantiate(self): assert ByteLevel() is not None...
tokenizers/bindings/python/tests/bindings/test_decoders.py/0
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# Tokenizer <tokenizerslangcontent> <python> ## Tokenizer [[autodoc]] tokenizers.Tokenizer - all - decoder - model - normalizer - padding - post_processor - pre_tokenizer - truncation </python> <rust> The Rust API Reference is available directly on the [Docs.rs](https://docs.rs/tokeniz...
tokenizers/docs/source-doc-builder/api/tokenizer.mdx/0
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.highlight .c1, .highlight .sd{ color: #999 } .highlight .nn, .highlight .k, .highlight .s1, .highlight .nb, .highlight .bp, .highlight .kc, .highlight .kt { color: #FB8D68; } .highlight .kn, .highlight .nv, .highlight .s2, .highlight .ow, .highlight .kd, .highlight .kr, .highlight .s { color: #6670FF; }...
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Quicktour ==================================================================================================== Let's have a quick look at the 🤗 Tokenizers library features. The library provides an implementation of today's most used tokenizers that is both easy to use and blazing fast. .. only:: python It can b...
tokenizers/docs/source/quicktour.rst/0
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{ "name": "create-wasm-app", "version": "0.1.0", "description": "create an app to consume rust-generated wasm packages", "main": "index.js", "bin": { "create-wasm-app": ".bin/create-wasm-app.js" }, "scripts": { "build": "webpack --config webpack.config.js", "start": "...
tokenizers/tokenizers/examples/unstable_wasm/www/package.json/0
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use super::Pair; use rand::{thread_rng, Rng}; use std::cmp::Ordering; use std::collections::{BinaryHeap, HashMap}; #[derive(Debug, Eq)] struct Merge { pos: usize, rank: u32, new_id: u32, } impl PartialEq for Merge { fn eq(&self, other: &Self) -> bool { self.rank == other.rank && self.pos == ot...
tokenizers/tokenizers/src/models/bpe/word.rs/0
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pub mod bert; pub mod byte_level; pub mod precompiled; pub mod prepend; pub mod replace; pub mod strip; pub mod unicode; pub mod utils; pub use crate::normalizers::bert::BertNormalizer; pub use crate::normalizers::byte_level::ByteLevel; pub use crate::normalizers::precompiled::Precompiled; pub use crate::normalizers::p...
tokenizers/tokenizers/src/normalizers/mod.rs/0
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mod pre_tokenizer; mod scripts; // Re-export the PreTokenizer pub use pre_tokenizer::UnicodeScripts;
tokenizers/tokenizers/src/pre_tokenizers/unicode_scripts/mod.rs/0
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use std::borrow::Borrow; use std::collections::HashMap; use std::hash::Hash; use std::sync::RwLock; /// The default capacity for a `BPE`'s internal cache. pub static DEFAULT_CACHE_CAPACITY: usize = 10_000; /// Provides a simple multithread cache to speed up BPE tokenization that will try to read values /// concurrent...
tokenizers/tokenizers/src/utils/cache.rs/0
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use tokenizers::models::bpe::BPE; use tokenizers::pre_tokenizers::whitespace::Whitespace; use tokenizers::{DecoderWrapper, NormalizerWrapper, PostProcessorWrapper, PreTokenizerWrapper}; use tokenizers::{Model, Tokenizer, TokenizerBuilder}; #[test] fn bpe_values_after_training() { let mut tokenizer = TokenizerBuild...
tokenizers/tokenizers/tests/training.rs/0
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FROM python:3.10-slim ENV PYTHONDONTWRITEBYTECODE=1 USER root ARG REF=main RUN apt-get update && apt-get install -y time git g++ pkg-config make git-lfs ENV UV_PYTHON=/usr/local/bin/python RUN pip install uv && uv venv && uv pip install --no-cache-dir -U pip setuptools GitPython RUN pip install --no-cache-dir --upgrade...
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ARG BASE_DOCKER_IMAGE FROM $BASE_DOCKER_IMAGE 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"] RUN apt update RUN apt install -y git libsndfile1-dev tesseract-ocr espea...
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- sections: - local: index title: 🤗 Transformers - local: quicktour title: Schnellstart - local: installation title: Installation title: Erste Schritte - sections: - local: pipeline_tutorial title: Pipelines für Inferenzen - local: autoclass_tutorial title: Laden von vortrainierten Inst...
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transformers/docs/source/en/main_classes/data_collator.md/0
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transformers/docs/source/en/model_doc/albert.md/0
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transformers/docs/source/en/model_doc/data2vec.md/0
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transformers/docs/source/en/model_doc/dit.md/0
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transformers/docs/source/en/model_doc/gpt_neox.md/0
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transformers/docs/source/en/model_doc/llava.md/0
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transformers/docs/source/en/model_doc/mbart.md/0
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transformers/docs/source/en/model_doc/mpt.md/0
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transformers/docs/source/en/model_doc/openai-gpt.md/0
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transformers/docs/source/en/model_doc/resnet.md/0
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transformers/docs/source/en/model_doc/speech-encoder-decoder.md/0
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transformers/docs/source/en/model_doc/table-transformer.md/0
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transformers/docs/source/en/model_doc/upernet.md/0
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transformers/docs/source/en/model_doc/vivit.md/0
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transformers/docs/source/en/model_doc/xlsr_wav2vec2.md/0
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transformers/docs/source/en/perf_train_cpu.md/0
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transformers/docs/source/en/tasks/semantic_segmentation.md/0
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transformers/docs/source/en/torchscript.md/0
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transformers/docs/source/es/debugging.md/0
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transformers/docs/source/it/add_new_pipeline.md/0
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transformers/docs/source/it/perf_infer_gpu_one.md/0
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transformers/docs/source/ja/model_doc/audio-spectrogram-transformer.md/0
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transformers/docs/source/ja/model_doc/blenderbot-small.md/0
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transformers/docs/source/ja/model_doc/code_llama.md/0
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transformers/docs/source/ja/model_doc/deplot.md/0
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transformers/docs/source/ja/perf_torch_compile.md/0
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transformers/docs/source/ja/run_scripts.md/0
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transformers/docs/source/ja/tasks/prompting.md/0
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transformers/docs/source/ja/tokenizer_summary.md/0
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transformers/docs/source/ko/main_classes/agent.md/0
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