text stringlengths 5 631k | id stringlengths 14 178 | metadata dict | __index_level_0__ int64 0 647 |
|---|---|---|---|
import inspect
from dataclasses import asdict, dataclass
from logging import getLogger
from typing import TYPE_CHECKING, Any, Callable, Type
from smolagents.models import ChatMessage, MessageRole, get_dict_from_nested_dataclasses
from smolagents.monitoring import AgentLogger, LogLevel, Timing, TokenUsage
from smolagen... | smolagents/src/smolagents/memory.py/0 | {
"file_path": "smolagents/src/smolagents/memory.py",
"repo_id": "smolagents",
"token_count": 5358
} | 287 |
# coding=utf-8
# Copyright 2024 HuggingFace 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 the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ag... | smolagents/tests/test_agents.py/0 | {
"file_path": "smolagents/tests/test_agents.py",
"repo_id": "smolagents",
"token_count": 46503
} | 288 |
import ast
from textwrap import dedent
import pytest
from smolagents.default_tools import (
DuckDuckGoSearchTool,
GoogleSearchTool,
SpeechToTextTool,
VisitWebpageTool,
WebSearchTool,
)
from smolagents.tool_validation import MethodChecker, validate_tool_attributes
from smolagents.tools import Tool,... | smolagents/tests/test_tool_validation.py/0 | {
"file_path": "smolagents/tests/test_tool_validation.py",
"repo_id": "smolagents",
"token_count": 2093
} | 289 |
# Rust builder
FROM lukemathwalker/cargo-chef:latest-rust-1.85.1 AS chef
WORKDIR /usr/src
ARG CARGO_REGISTRIES_CRATES_IO_PROTOCOL=sparse
FROM chef AS planner
COPY Cargo.lock Cargo.lock
COPY Cargo.toml Cargo.toml
COPY rust-toolchain.toml rust-toolchain.toml
COPY proto proto
COPY benchmark benchmark
COPY router router
... | text-generation-inference/Dockerfile_amd/0 | {
"file_path": "text-generation-inference/Dockerfile_amd",
"repo_id": "text-generation-inference",
"token_count": 4709
} | 290 |
#[allow(clippy::derive_partial_eq_without_eq)]
mod pb;
mod client;
mod sharded_client;
pub use client::Client;
pub use pb::generate::v2::HealthResponse;
pub use pb::generate::v2::{
Batch, CachedBatch, FinishReason, GeneratedText, Generation, GrammarType, InfoResponse,
NextTokenChooserParameters, Request, Stop... | text-generation-inference/backends/client/src/v2/mod.rs/0 | {
"file_path": "text-generation-inference/backends/client/src/v2/mod.rs",
"repo_id": "text-generation-inference",
"token_count": 134
} | 291 |
commit_cuda := d243e9dc7e2c9c2e36a4150ec8e64809cb55c01b
commit_rocm := 4e0929e6e4fa0a3d09d358715c288020ea9dc247
build-vllm-cuda:
if [ ! -d 'vllm' ]; then \
pip install -U ninja packaging --no-cache-dir && \
git clone https://github.com/Narsil/vllm.git vllm; \
fi
cd vllm && git fetch origin && git checkout $(com... | text-generation-inference/backends/gaudi/server/Makefile-vllm/0 | {
"file_path": "text-generation-inference/backends/gaudi/server/Makefile-vllm",
"repo_id": "text-generation-inference",
"token_count": 397
} | 292 |
from .common import (
Seqlen,
HPUPagedAttentionMetadata,
trim_attn_metadata,
trim_seqlen_metadata,
_async_h2d_tensor_copy,
)
from .hpu import (
SUPPORTS_WINDOWING,
attention,
paged_attention,
paged_attention_mla,
set_block_mapping,
)
# KVCache needs `reshape_and_cache`, so ens... | text-generation-inference/backends/gaudi/server/text_generation_server/layers/attention/__init__.py/0 | {
"file_path": "text-generation-inference/backends/gaudi/server/text_generation_server/layers/attention/__init__.py",
"repo_id": "text-generation-inference",
"token_count": 344
} | 293 |
# coding=utf-8
# Copyright 2022 HuggingFace Inc. team and BigScience workshop.
#
# 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 re... | text-generation-inference/backends/gaudi/server/text_generation_server/models/custom_modeling/bloom_modeling.py/0 | {
"file_path": "text-generation-inference/backends/gaudi/server/text_generation_server/models/custom_modeling/bloom_modeling.py",
"repo_id": "text-generation-inference",
"token_count": 16226
} | 294 |
from typing import Optional, Tuple
import warnings
import math
import torch
from torch import nn
from transformers.activations import ACT2FN
from transformers.modeling_outputs import (
BaseModelOutputWithPooling,
)
from transformers import SiglipConfig, SiglipVisionConfig
from torch.nn.init import _calculate_fan_i... | text-generation-inference/backends/gaudi/server/text_generation_server/models/custom_modeling/siglip.py/0 | {
"file_path": "text-generation-inference/backends/gaudi/server/text_generation_server/models/custom_modeling/siglip.py",
"repo_id": "text-generation-inference",
"token_count": 6676
} | 295 |
# Copyright (C) 2024 Habana Labs, Ltd. an Intel Company.
import os
import glob
import time
import habana_frameworks.torch as htorch
import numpy as np
START_TS = None
DBG_TRACE_FILENAME = os.environ.get("DBG_TRACE_FILENAME")
if "GRAPH_VISUALIZATION" in os.environ:
for f in glob.glob(".graph_dumps/*"):
os... | text-generation-inference/backends/gaudi/server/text_generation_server/utils/debug.py/0 | {
"file_path": "text-generation-inference/backends/gaudi/server/text_generation_server/utils/debug.py",
"repo_id": "text-generation-inference",
"token_count": 613
} | 296 |
from packaging.version import Version
from packaging import version
import subprocess
def get_driver_version():
"""
Returns the driver version.
"""
# Enable console printing for `hl-smi` check
output = subprocess.run(
"hl-smi",
shell=True,
text=True,
stdout=subproce... | text-generation-inference/backends/gaudi/server/text_generation_server/utils/version.py/0 | {
"file_path": "text-generation-inference/backends/gaudi/server/text_generation_server/utils/version.py",
"repo_id": "text-generation-inference",
"token_count": 412
} | 297 |
# Text-generation-inference - Neuron backend for AWS Trainium and inferentia2
## Description
This is the TGI backend for AWS Neuron Trainium and Inferentia family of chips.
This backend is composed of:
- the AWS Neuron SDK,
- the legacy v2 TGI launcher and router,
- a neuron specific inference server for text-genera... | text-generation-inference/backends/neuron/README.md/0 | {
"file_path": "text-generation-inference/backends/neuron/README.md",
"repo_id": "text-generation-inference",
"token_count": 211
} | 298 |
from text_generation_server.generator import NeuronGenerator
from text_generation_server.pb.generate_pb2 import (
Batch,
NextTokenChooserParameters,
Request,
StoppingCriteriaParameters,
)
def create_request(
id: int,
inputs: str,
truncate: int = 0,
max_new_tokens: int = 20,
do_samp... | text-generation-inference/backends/neuron/tests/server/helpers.py/0 | {
"file_path": "text-generation-inference/backends/neuron/tests/server/helpers.py",
"repo_id": "text-generation-inference",
"token_count": 2593
} | 299 |
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
} | 300 |
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
} | 301 |
- 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": 924
} | 302 |
# TGI v3 overview
## Summary
Performance leap: TGI processes 3x more tokens, 13x faster than vLLM on long prompts. Zero config !
### 3x more tokens.
By reducing our memory footprint, we’re able to ingest many more tokens and more dynamically than before. A single L4 (24GB) can handle 30k tokens on llama 3.1-8B, whil... | text-generation-inference/docs/source/conceptual/chunking.md/0 | {
"file_path": "text-generation-inference/docs/source/conceptual/chunking.md",
"repo_id": "text-generation-inference",
"token_count": 2789
} | 303 |
# Using TGI with Intel GPUs
TGI optimized models are supported on Intel Data Center GPU [Max1100](https://www.intel.com/content/www/us/en/products/sku/232876/intel-data-center-gpu-max-1100/specifications.html), [Max1550](https://www.intel.com/content/www/us/en/products/sku/232873/intel-data-center-gpu-max-1550/specifi... | text-generation-inference/docs/source/installation_intel.md/0 | {
"file_path": "text-generation-inference/docs/source/installation_intel.md",
"repo_id": "text-generation-inference",
"token_count": 562
} | 304 |
import json
import os
from typing import Dict, Any, Generator
import pytest
from test_gaudi_generate import TEST_CONFIGS
UNKNOWN_CONFIGS = {
name: config
for name, config in TEST_CONFIGS.items()
if config["expected_greedy_output"] == "unknown"
or config["expected_batch_output"] == "unknown"
}
@pytes... | text-generation-inference/integration-tests/gaudi/capture_expected_outputs.py/0 | {
"file_path": "text-generation-inference/integration-tests/gaudi/capture_expected_outputs.py",
"repo_id": "text-generation-inference",
"token_count": 947
} | 305 |
[
{
"choices": [
{
"finish_reason": "",
"index": 0,
"logprobs": null,
"text": " A"
}
],
"created": 1741340006,
"id": "",
"model": "meta-llama/Llama-3.1-8B-Instruct",
"object": "text_completion",
"system_fingerprint": "3.1.2-dev0-native",
"usa... | text-generation-inference/integration-tests/models/__snapshots__/test_completion_prompts/test_flash_llama_completion_many_prompts_stream.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_completion_prompts/test_flash_llama_completion_many_prompts_stream.json",
"repo_id": "text-generation-inference",
"token_count": 7648
} | 306 |
[
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [],
"seed": null,
"tokens": [
{
"id": 1736,
"logprob": -2.09375,
"special": false,
"text": " form"
},
{
... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_gemma/test_flash_gemma_load.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_gemma/test_flash_gemma_load.json",
"repo_id": "text-generation-inference",
"token_count": 4072
} | 307 |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [],
"seed": null,
"tokens": [
{
"id": 13,
"logprob": -2.0566406,
"special": false,
"text": "\n"
},
{
"id": 13,
"logprob": -1... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_grammar_llama/test_flash_llama_grammar.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_grammar_llama/test_flash_llama_grammar.json",
"repo_id": "text-generation-inference",
"token_count": 866
} | 308 |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [],
"seed": 0,
"tokens": [
{
"id": 28747,
"logprob": 0.0,
"special": false,
"text": ":"
},
{
"id": 3169,
"logprob": -0.13073... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_mistral/test_flash_mistral_all_params.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_mistral/test_flash_mistral_all_params.json",
"repo_id": "text-generation-inference",
"token_count": 856
} | 309 |
{
"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
} | 310 |
{
"choices": [
{
"finish_reason": "stop",
"index": 0,
"logprobs": null,
"message": {
"content": "The image shows a stylized scene set in what appears to be a diner or restaurant. In the foreground, there is a table with various food items, including a burger with lettuce and tomato... | text-generation-inference/integration-tests/models/__snapshots__/test_flash_qwen2_vl/test_flash_qwen2_vl_inpaint.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_qwen2_vl/test_flash_qwen2_vl_inpaint.json",
"repo_id": "text-generation-inference",
"token_count": 422
} | 311 |
[
{
"choices": [
{
"delta": {
"content": "{",
"role": "assistant"
},
"finish_reason": null,
"index": 0,
"logprobs": null
}
],
"created": 1741975615,
"id": "",
"model": "google/gemma-3-4b-it",
"object": "chat.completion.chu... | text-generation-inference/integration-tests/models/__snapshots__/test_json_schema_constrain/test_json_schema_stream.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_json_schema_constrain/test_json_schema_stream.json",
"repo_id": "text-generation-inference",
"token_count": 8555
} | 312 |
{
"details": {
"best_of_sequences": null,
"finish_reason": "length",
"generated_tokens": 10,
"prefill": [
{
"id": 0,
"logprob": null,
"text": "<pad>"
}
],
"seed": 0,
"tokens": [
{
"id": 16017,
"logprob": 0.0,
"special": fals... | text-generation-inference/integration-tests/models/__snapshots__/test_mt0_base/test_mt0_base_all_params.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_mt0_base/test_mt0_base_all_params.json",
"repo_id": "text-generation-inference",
"token_count": 910
} | 313 |
[
{
"choices": [
{
"delta": {
"content": "I",
"role": "assistant",
"tool_calls": null
},
"finish_reason": null,
"index": 0,
"logprobs": null
}
],
"created": 1741694017,
"id": "",
"model": "meta-llama/Llama-3.1-8B-Ins... | text-generation-inference/integration-tests/models/__snapshots__/test_tools_llama/test_flash_llama_grammar_tools_insufficient_information_stream.json/0 | {
"file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_tools_llama/test_flash_llama_grammar_tools_insufficient_information_stream.json",
"repo_id": "text-generation-inference",
"token_count": 4844
} | 314 |
import pytest
@pytest.fixture(scope="module")
def bloom_560_handle(launcher):
with launcher("bigscience/bloom-560m", num_shard=1) as handle:
yield handle
@pytest.fixture(scope="module")
async def bloom_560(bloom_560_handle):
await bloom_560_handle.health(240)
return bloom_560_handle.client
@py... | text-generation-inference/integration-tests/models/test_bloom_560m.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_bloom_560m.py",
"repo_id": "text-generation-inference",
"token_count": 783
} | 315 |
import pytest
@pytest.fixture(scope="module")
def flash_gemma2_handle(launcher):
with launcher("google/gemma-2-9b-it", num_shard=2) as handle:
yield handle
@pytest.fixture(scope="module")
async def flash_gemma2(flash_gemma2_handle):
await flash_gemma2_handle.health(300)
return flash_gemma2_handl... | text-generation-inference/integration-tests/models/test_flash_gemma2.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_flash_gemma2.py",
"repo_id": "text-generation-inference",
"token_count": 602
} | 316 |
import pytest
@pytest.fixture(scope="module")
def flash_mixtral_handle(launcher):
with launcher("mistralai/Mixtral-8x7B-v0.1", num_shard=8) as handle:
yield handle
@pytest.fixture(scope="module")
async def flash_mixtral(flash_mixtral_handle):
await flash_mixtral_handle.health(300)
return flash_m... | text-generation-inference/integration-tests/models/test_flash_mixtral.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_flash_mixtral.py",
"repo_id": "text-generation-inference",
"token_count": 926
} | 317 |
import pytest
@pytest.fixture(scope="module")
def flash_starcoder_gptq_handle(launcher):
with launcher("Narsil/starcoder-gptq", num_shard=2, quantize="gptq") as handle:
yield handle
@pytest.fixture(scope="module")
async def flash_starcoder_gptq(flash_starcoder_gptq_handle):
await flash_starcoder_gpt... | text-generation-inference/integration-tests/models/test_flash_starcoder_gptq.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_flash_starcoder_gptq.py",
"repo_id": "text-generation-inference",
"token_count": 802
} | 318 |
import pytest
@pytest.fixture(scope="module")
def flash_smolvlm_next_handle(launcher):
with launcher("HuggingFaceTB/SmolVLM-Instruct") as handle:
yield handle
@pytest.fixture(scope="module")
async def flash_smolvlm_next(flash_smolvlm_next_handle):
await flash_smolvlm_next_handle.health(300)
retu... | text-generation-inference/integration-tests/models/test_smolvlm.py/0 | {
"file_path": "text-generation-inference/integration-tests/models/test_smolvlm.py",
"repo_id": "text-generation-inference",
"token_count": 435
} | 319 |
ShareGPT_V3_unfiltered_cleaned_split.json:
wget https://huggingface.co/datasets/anon8231489123/ShareGPT_Vicuna_unfiltered/resolve/main/ShareGPT_V3_unfiltered_cleaned_split.json
prepare_share: ShareGPT_V3_unfiltered_cleaned_split.json
python filter.py
prepare_orca:
python orca.py
| text-generation-inference/load_tests/Makefile/0 | {
"file_path": "text-generation-inference/load_tests/Makefile",
"repo_id": "text-generation-inference",
"token_count": 123
} | 320 |
syntax = "proto3";
package generate.v2;
service TextGenerationService {
/// Model Info
rpc Info (InfoRequest) returns (InfoResponse) {}
/// Service discovery
rpc ServiceDiscovery (ServiceDiscoveryRequest) returns (ServiceDiscoveryResponse) {}
/// Empties batch cache
rpc ClearCache (ClearCacheR... | text-generation-inference/proto/generate.proto/0 | {
"file_path": "text-generation-inference/proto/generate.proto",
"repo_id": "text-generation-inference",
"token_count": 2074
} | 321 |
use crate::config::Config;
use crate::validation::ValidationError::{BestOfSampling, BestOfSeed, EmptyInput};
use crate::{
GenerateParameters, GenerateRequest, GrammarType, HubPreprocessorConfig, Idefics2Preprocessor,
TokenizerTrait,
};
use crate::{PyTokenizer, Tokenizer};
use base64::{engine::general_purpose::S... | text-generation-inference/router/src/validation.rs/0 | {
"file_path": "text-generation-inference/router/src/validation.rs",
"repo_id": "text-generation-inference",
"token_count": 25286
} | 322 |
#include <ATen/Dispatch.h>
#include <THC/THCAtomics.cuh>
#include <ATen/ATen.h>
#include <torch/torch.h>
#include <vector>
#include <optional>
/**
* Friendly reminder of how multithreading works in CUDA: https://developer.nvidia.com/blog/even-easier-introduction-cuda
* Check example at https://github.com/thomasw21/Li... | text-generation-inference/server/custom_kernels/custom_kernels/fused_attention_cuda.cu/0 | {
"file_path": "text-generation-inference/server/custom_kernels/custom_kernels/fused_attention_cuda.cu",
"repo_id": "text-generation-inference",
"token_count": 5265
} | 323 |
// Adapted from turboderp exllama: https://github.com/turboderp/exllama
#ifndef _util_cuh
#define _util_cuh
#include <cuda_runtime.h>
#include <cuda_fp16.h>
#include <cstdint>
#include <cstdio>
#if defined(USE_ROCM)
#define cudaUnspecified hipErrorUnknown
#else
#define cudaUnspecified cudaErrorApiFailureBase
#endif
... | text-generation-inference/server/exllama_kernels/exllama_kernels/util.cuh/0 | {
"file_path": "text-generation-inference/server/exllama_kernels/exllama_kernels/util.cuh",
"repo_id": "text-generation-inference",
"token_count": 283
} | 324 |
#ifndef _qdq_6_cuh
#define _qdq_6_cuh
#include "qdq_util.cuh"
#include "../../config.h"
#if QMODE_6BIT == 1
// Not implemented
#else
__forceinline__ __device__ void shuffle_6bit_16
(
uint32_t* q,
int stride
)
{
}
__forceinline__ __device__ void dequant_6bit_16
(
const uint32_t q_0,
const uint32_... | text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/quant/qdq_6.cuh/0 | {
"file_path": "text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/quant/qdq_6.cuh",
"repo_id": "text-generation-inference",
"token_count": 571
} | 325 |
import pytest
import torch
from transformers import AutoTokenizer
from text_generation_server.models import Model
def get_test_model():
class TestModel(Model):
def batch_type(self):
raise NotImplementedError
def generate_token(self, batch):
raise NotImplementedError
... | text-generation-inference/server/tests/models/test_model.py/0 | {
"file_path": "text-generation-inference/server/tests/models/test_model.py",
"repo_id": "text-generation-inference",
"token_count": 876
} | 326 |
from .loader import CompressedTensorsLoader
__all__ = ["CompressedTensorsLoader"]
| text-generation-inference/server/text_generation_server/layers/compressed_tensors/__init__.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/layers/compressed_tensors/__init__.py",
"repo_id": "text-generation-inference",
"token_count": 25
} | 327 |
import math
import numpy as np
import torch
import torch.nn as nn
from torch.cuda.amp import custom_fwd
import triton
import triton.language as tl
from . import custom_autotune
# code based https://github.com/fpgaminer/GPTQ-triton
@custom_autotune.autotune(
configs=[
triton.Config(
{
... | text-generation-inference/server/text_generation_server/layers/gptq/triton.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/layers/gptq/triton.py",
"repo_id": "text-generation-inference",
"token_count": 6339
} | 328 |
from typing import Callable, List, Optional
import torch
import torch.nn as nn
from text_generation_server.utils.import_utils import SYSTEM
from text_generation_server.utils.kernels import load_kernel
from text_generation_server.utils.weights import UnquantizedWeight, Weights
if SYSTEM == "ipex":
from intel_exte... | text-generation-inference/server/text_generation_server/layers/moe/unquantized.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/layers/moe/unquantized.py",
"repo_id": "text-generation-inference",
"token_count": 4359
} | 329 |
# coding=utf-8
# Copyright 2025 Google Inc. 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
#
... | text-generation-inference/server/text_generation_server/models/custom_modeling/gemma3/processing_gemma3.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/models/custom_modeling/gemma3/processing_gemma3.py",
"repo_id": "text-generation-inference",
"token_count": 3387
} | 330 |
# imlementation of the PhiModel and PhiForCausalLM classes
import torch
import torch.distributed
import math
from torch import nn
from typing import Optional, List, Tuple
from transformers.configuration_utils import PretrainedConfig
from transformers.modeling_outputs import CausalLMOutputWithPast
from text_generatio... | text-generation-inference/server/text_generation_server/models/custom_modeling/phi_modeling.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/models/custom_modeling/phi_modeling.py",
"repo_id": "text-generation-inference",
"token_count": 5696
} | 331 |
import math
from typing import List, Optional
import torch
from opentelemetry import trace
from transformers import AutoTokenizer, AutoProcessor
import transformers.modeling_utils
from text_generation_server.models.flash_causal_lm import FlashCausalLM
from text_generation_server.models.vlm_causal_lm import VlmCausalL... | text-generation-inference/server/text_generation_server/models/transformers_flash_vlm.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/models/transformers_flash_vlm.py",
"repo_id": "text-generation-inference",
"token_count": 11604
} | 332 |
import copy
from abc import ABC
from collections import defaultdict
from typing import TYPE_CHECKING, Dict, List, Tuple, Type, Union
from text_generation_server.utils.merges.utils import (
calculate_majority_sign_mask,
disjoint_merge,
prune,
)
import torch
if TYPE_CHECKING:
from text_generation_server.... | text-generation-inference/server/text_generation_server/utils/merges/strategies.py/0 | {
"file_path": "text-generation-inference/server/text_generation_server/utils/merges/strategies.py",
"repo_id": "text-generation-inference",
"token_count": 3074
} | 333 |
## How to release
# Before the release
Simple checklist on how to make releases for `tokenizers`.
- Freeze `master` branch.
- Run all tests (Check CI has properly run)
- If any significant work, check benchmarks:
- `cd tokenizers && cargo bench` (needs to be run on latest release tag to measure difference if it's ... | tokenizers/RELEASE.md/0 | {
"file_path": "tokenizers/RELEASE.md",
"repo_id": "tokenizers",
"token_count": 1519
} | 334 |
/* eslint-disable */
var globRequire = require
console.log = (..._args: any[]) => {}
describe('quicktourExample', () => {
function require(mod: string) {
if (mod.startsWith('tokenizers')) {
return globRequire('../../')
} else {
return globRequire(mod)
}
}
it.skip('trains the tokenizer',... | tokenizers/bindings/node/examples/documentation/quicktour.test.ts/0 | {
"file_path": "tokenizers/bindings/node/examples/documentation/quicktour.test.ts",
"repo_id": "tokenizers",
"token_count": 2324
} | 335 |
{
"name": "tokenizers-android-arm-eabi",
"version": "0.13.4-rc1",
"os": [
"android"
],
"cpu": [
"arm"
],
"main": "tokenizers.android-arm-eabi.node",
"files": [
"tokenizers.android-arm-eabi.node"
],
"description": "Tokenizers platform specific bindings",
"keywords": [
"napi-rs",
... | tokenizers/bindings/node/npm/android-arm-eabi/package.json/0 | {
"file_path": "tokenizers/bindings/node/npm/android-arm-eabi/package.json",
"repo_id": "tokenizers",
"token_count": 269
} | 336 |
{
"name": "tokenizers-linux-x64-gnu",
"version": "0.13.4-rc1",
"os": [
"linux"
],
"cpu": [
"x64"
],
"main": "tokenizers.linux-x64-gnu.node",
"files": [
"tokenizers.linux-x64-gnu.node"
],
"description": "Tokenizers platform specific bindings",
"keywords": [
"napi-rs",
"NAPI",
... | tokenizers/bindings/node/npm/linux-x64-gnu/package.json/0 | {
"file_path": "tokenizers/bindings/node/npm/linux-x64-gnu/package.json",
"repo_id": "tokenizers",
"token_count": 289
} | 337 |
use crate::arc_rwlock_serde;
use napi::bindgen_prelude::*;
use napi_derive::napi;
use serde::{Deserialize, Serialize};
use std::sync::{Arc, RwLock};
use tk::normalizers::NormalizerWrapper;
use tk::NormalizedString;
use tokenizers as tk;
/// Normalizer
#[derive(Debug, Clone, Serialize, Deserialize)]
#[napi]
pub struct ... | tokenizers/bindings/node/src/normalizers.rs/0 | {
"file_path": "tokenizers/bindings/node/src/normalizers.rs",
"repo_id": "tokenizers",
"token_count": 1885
} | 338 |
include Cargo.toml
include pyproject.toml
include rust-toolchain
include ../../LICENSE
recursive-include src *
recursive-include tokenizers-lib *
recursive-exclude tokenizers-lib/target *
| tokenizers/bindings/python/MANIFEST.in/0 | {
"file_path": "tokenizers/bindings/python/MANIFEST.in",
"repo_id": "tokenizers",
"token_count": 57
} | 339 |
from typing import Dict, List, Optional, Tuple, Union
from tokenizers import AddedToken, EncodeInput, Encoding, InputSequence, Tokenizer
from tokenizers.decoders import Decoder
from tokenizers.models import Model
from tokenizers.normalizers import Normalizer
from tokenizers.pre_tokenizers import PreTokenizer
from toke... | tokenizers/bindings/python/py_src/tokenizers/implementations/base_tokenizer.py/0 | {
"file_path": "tokenizers/bindings/python/py_src/tokenizers/implementations/base_tokenizer.py",
"repo_id": "tokenizers",
"token_count": 6036
} | 340 |
import itertools
import os
import re
from string import Template
from typing import Any, Callable, Dict, List, NamedTuple, Optional, Tuple
from tokenizers import Encoding, Tokenizer
dirname = os.path.dirname(__file__)
css_filename = os.path.join(dirname, "visualizer-styles.css")
with open(css_filename) as f:
css... | tokenizers/bindings/python/py_src/tokenizers/tools/visualizer.py/0 | {
"file_path": "tokenizers/bindings/python/py_src/tokenizers/tools/visualizer.py",
"repo_id": "tokenizers",
"token_count": 6751
} | 341 |
use std::convert::TryInto;
use std::sync::Arc;
use std::sync::RwLock;
use crate::encoding::PyEncoding;
use crate::error::ToPyResult;
use pyo3::exceptions;
use pyo3::exceptions::PyException;
use pyo3::prelude::*;
use pyo3::types::*;
use serde::ser::SerializeStruct;
use serde::Deserializer;
use serde::Serializer;
use se... | tokenizers/bindings/python/src/processors.rs/0 | {
"file_path": "tokenizers/bindings/python/src/processors.rs",
"repo_id": "tokenizers",
"token_count": 14503
} | 342 |
import pickle
import pytest
from tokenizers.models import BPE, Model, WordLevel, WordPiece
from ..utils import bert_files, data_dir, roberta_files
class TestBPE:
def test_instantiate(self, roberta_files):
assert isinstance(BPE(), Model)
assert isinstance(BPE(), BPE)
vocab = {"a": 0, "b"... | tokenizers/bindings/python/tests/bindings/test_models.py/0 | {
"file_path": "tokenizers/bindings/python/tests/bindings/test_models.py",
"repo_id": "tokenizers",
"token_count": 2304
} | 343 |
# Visualizer
<tokenizerslangcontent>
<python>
## Annotation
[[autodoc]] tokenizers.tools.Annotation
## EncodingVisualizer
[[autodoc]] tokenizers.tools.EncodingVisualizer
- __call__
</python>
<rust>
The Rust API Reference is available directly on the [Docs.rs](https://docs.rs/tokenizers/latest/tokenizers/) webs... | tokenizers/docs/source-doc-builder/api/visualizer.mdx/0 | {
"file_path": "tokenizers/docs/source-doc-builder/api/visualizer.mdx",
"repo_id": "tokenizers",
"token_count": 134
} | 344 |
# 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]
- Python only changes
## [0.13.1]
- [#1072] Fixing ... | tokenizers/tokenizers/CHANGELOG.md/0 | {
"file_path": "tokenizers/tokenizers/CHANGELOG.md",
"repo_id": "tokenizers",
"token_count": 3387
} | 345 |
<div align="center">
<h1><code>wasm-pack-template</code></h1>
<strong>A template for kick starting a Rust and WebAssembly project using <a href="https://github.com/rustwasm/wasm-pack">wasm-pack</a>.</strong>
<p>
<a href="https://travis-ci.org/rustwasm/wasm-pack-template"><img src="https://img.shields.io/tr... | tokenizers/tokenizers/examples/unstable_wasm/README.md/0 | {
"file_path": "tokenizers/tokenizers/examples/unstable_wasm/README.md",
"repo_id": "tokenizers",
"token_count": 811
} | 346 |
stable
| tokenizers/tokenizers/rust-toolchain/0 | {
"file_path": "tokenizers/tokenizers/rust-toolchain",
"repo_id": "tokenizers",
"token_count": 2
} | 347 |
use dary_heap::QuaternaryHeap;
use rand::distr::weighted::WeightedIndex;
use rand::{prelude::*, rng};
use std::cell::RefCell;
use std::cmp::{min, Ordering};
use std::rc::Rc;
type NodeRef = Rc<RefCell<Node>>;
type HypothesisRef = Rc<RefCell<Hypothesis>>;
type Agenda = QuaternaryHeap<Hypothesis>;
struct Hypothesis {
... | tokenizers/tokenizers/src/models/unigram/lattice.rs/0 | {
"file_path": "tokenizers/tokenizers/src/models/unigram/lattice.rs",
"repo_id": "tokenizers",
"token_count": 12693
} | 348 |
use crate::tokenizer::{NormalizedString, Normalizer, Result};
use serde::{Deserialize, Serialize};
#[derive(Clone, Debug, Deserialize, Serialize)]
#[serde(tag = "type")]
pub struct Prepend {
pub prepend: String,
}
impl Prepend {
pub fn new(prepend: String) -> Self {
Self { prepend }
}
}
impl Norm... | tokenizers/tokenizers/src/normalizers/prepend.rs/0 | {
"file_path": "tokenizers/tokenizers/src/normalizers/prepend.rs",
"repo_id": "tokenizers",
"token_count": 856
} | 349 |
use crate::pre_tokenizers::unicode_scripts::scripts::{get_script, Script};
use crate::tokenizer::{normalizer::Range, PreTokenizedString, PreTokenizer, Result};
use crate::utils::macro_rules_attribute;
#[derive(Clone, Debug, PartialEq, Eq)]
#[macro_rules_attribute(impl_serde_type!)]
pub struct UnicodeScripts;
impl Uni... | tokenizers/tokenizers/src/pre_tokenizers/unicode_scripts/pre_tokenizer.rs/0 | {
"file_path": "tokenizers/tokenizers/src/pre_tokenizers/unicode_scripts/pre_tokenizer.rs",
"repo_id": "tokenizers",
"token_count": 2584
} | 350 |
use crate::tokenizer::pattern::Pattern;
use crate::Offsets;
use fancy_regex::Regex;
use std::error::Error;
#[derive(Debug)]
pub struct SysRegex {
regex: Regex,
}
impl SysRegex {
pub fn find_iter<'r, 't>(&'r self, inside: &'t str) -> Matches<'r, 't> {
Matches(self.regex.find_iter(inside))
}
pu... | tokenizers/tokenizers/src/utils/fancy.rs/0 | {
"file_path": "tokenizers/tokenizers/src/utils/fancy.rs",
"repo_id": "tokenizers",
"token_count": 823
} | 351 |
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 | {
"file_path": "tokenizers/tokenizers/tests/training.rs",
"repo_id": "tokenizers",
"token_count": 851
} | 352 |
# Accessing Private/Gated Models
<Tip>
Due to the possibility of leaking access tokens to users of your website or web application, we only support accessing private/gated models from server-side environments (e.g., Node.js) that have access to the process' environment variables.
</Tip>
## Step 1: Generating a Use... | transformers.js/docs/source/guides/private.md/0 | {
"file_path": "transformers.js/docs/source/guides/private.md",
"repo_id": "transformers.js",
"token_count": 711
} | 353 |
import React from 'react'
import ReactDOM from 'react-dom/client'
import App from './App.jsx'
import './index.css'
ReactDOM.createRoot(document.getElementById('root')).render(
<React.StrictMode>
<App />
</React.StrictMode>,
)
| transformers.js/examples/cross-encoder/src/main.jsx/0 | {
"file_path": "transformers.js/examples/cross-encoder/src/main.jsx",
"repo_id": "transformers.js",
"token_count": 87
} | 354 |
* {
box-sizing: border-box;
padding: 0;
margin: 0;
font-family: sans-serif;
}
html,
body {
height: 100%;
}
body {
padding: 16px 32px;
}
body,
#container,
#upload-button {
display: flex;
flex-direction: column;
justify-content: center;
align-items: center;
}
h1 {
text-align: center;
}
#contain... | transformers.js/examples/depth-anything-client/style.css/0 | {
"file_path": "transformers.js/examples/depth-anything-client/style.css",
"repo_id": "transformers.js",
"token_count": 474
} | 355 |
{
"name": "extension",
"version": "0.0.1",
"description": "Transformers.js | Sample browser extension",
"scripts": {
"build": "webpack",
"dev": "webpack --watch"
},
"type": "module",
"author": "Xenova",
"license": "MIT",
"devDependencies": {
"copy-webpack-plugin": "^11.0.0",
"html-webp... | transformers.js/examples/extension/package.json/0 | {
"file_path": "transformers.js/examples/extension/package.json",
"repo_id": "transformers.js",
"token_count": 198
} | 356 |
import { useState, useRef } from 'react';
const EXAMPLE_URL = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/beetle.png';
const ImageInput = ({ onImageChange, ...props }) => {
const [imagePreview, setImagePreview] = useState(null);
const fileInputRef = useRef(null);
const readF... | transformers.js/examples/florence2-webgpu/src/components/ImageInput.jsx/0 | {
"file_path": "transformers.js/examples/florence2-webgpu/src/components/ImageInput.jsx",
"repo_id": "transformers.js",
"token_count": 1106
} | 357 |
import './globals.css'
import { Inter } from 'next/font/google'
const inter = Inter({ subsets: ['latin'] })
export const metadata = {
title: 'Create Next App',
description: 'Generated by create next app',
}
export default function RootLayout({ children }) {
return (
<html lang="en">
<body className={... | transformers.js/examples/next-client/src/app/layout.js/0 | {
"file_path": "transformers.js/examples/next-client/src/app/layout.js",
"repo_id": "transformers.js",
"token_count": 128
} | 358 |
// Create a custom request handler for the /classify route.
// For more information, see https://nextjs.org/docs/app/building-your-application/routing/router-handlers
import { NextResponse } from 'next/server'
import PipelineSingleton from './pipeline.js';
export async function GET(request) {
const text = request... | transformers.js/examples/next-server/src/app/classify/route.js/0 | {
"file_path": "transformers.js/examples/next-server/src/app/classify/route.js",
"repo_id": "transformers.js",
"token_count": 250
} | 359 |
#root {
max-width: 1280px;
margin: 0 auto;
padding: 2rem;
text-align: center;
}
.language-container {
display: flex;
gap: 20px;
}
.textbox-container {
display: flex;
justify-content: center;
gap: 20px;
width: 800px;
}
.textbox-container>textarea, .language-selector {
width: 50%;
}
.language-se... | transformers.js/examples/react-translator/src/App.css/0 | {
"file_path": "transformers.js/examples/react-translator/src/App.css",
"repo_id": "transformers.js",
"token_count": 383
} | 360 |
This is a [Next.js](https://nextjs.org/) project bootstrapped with [`create-next-app`](https://github.com/vercel/next.js/tree/canary/packages/create-next-app).
## Getting Started
First, run the development server:
```bash
npm run dev
# or
yarn dev
# or
pnpm dev
```
Open [http://localhost:3000](http://localhost:3000... | transformers.js/examples/semantic-image-search-client/README.md/0 | {
"file_path": "transformers.js/examples/semantic-image-search-client/README.md",
"repo_id": "transformers.js",
"token_count": 413
} | 361 |
import { env, AutoTokenizer, CLIPTextModelWithProjection } from '@xenova/transformers';
import { getCachedFile, getCachedJSON } from './utils.js';
const EMBED_DIM = 512;
// Skip local model check
env.allowLocalModels = false;
class ApplicationSingleton {
static model_id = 'Xenova/clip-vit-base-patch16';
sta... | transformers.js/examples/semantic-image-search-client/src/app/worker.js/0 | {
"file_path": "transformers.js/examples/semantic-image-search-client/src/app/worker.js",
"repo_id": "transformers.js",
"token_count": 1518
} | 362 |
import Image from 'next/image'
import { blurHashToDataURL } from '../utils.js'
export function ImageGrid({ images, setCurrentImage }) {
return (
<div className="columns-2 gap-4 sm:columns-3 xl:columns-4 2xl:columns-5">
{images && images.map(({
photo_id,
photo_url... | transformers.js/examples/semantic-image-search/src/app/components/ImageGrid.jsx/0 | {
"file_path": "transformers.js/examples/semantic-image-search/src/app/components/ImageGrid.jsx",
"repo_id": "transformers.js",
"token_count": 1339
} | 363 |
import React, { useState, useEffect, useRef } from 'react';
import AudioPlayer from './components/AudioPlayer';
import Progress from './components/Progress';
import { SPEAKERS, DEFAULT_SPEAKER } from './constants';
const App = () => {
// Model loading
const [ready, setReady] = useState(null);
const [disabled, ... | transformers.js/examples/text-to-speech-client/src/App.jsx/0 | {
"file_path": "transformers.js/examples/text-to-speech-client/src/App.jsx",
"repo_id": "transformers.js",
"token_count": 2478
} | 364 |
import './style.css';
import { env, AutoModel, ones } from '@xenova/transformers';
import Chart from 'chart.js/auto';
// Throw an error if WebGPU is not supported
if (!navigator.gpu) {
const err = 'WebGPU is not supported by this browser.';
alert(err)
throw Error(err);
}
env.backends.onnx.wasm.wasmPaths = 'http... | transformers.js/examples/webgpu-embedding-benchmark/main.js/0 | {
"file_path": "transformers.js/examples/webgpu-embedding-benchmark/main.js",
"repo_id": "transformers.js",
"token_count": 3269
} | 365 |
export default function StopIcon(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/StopIcon.jsx/0 | {
"file_path": "transformers.js/examples/webgpu-vlm/src/components/icons/StopIcon.jsx",
"repo_id": "transformers.js",
"token_count": 375
} | 366 |
import { useRef, useCallback, useEffect } from "react";
export function AudioVisualizer({ stream, ...props }) {
const canvasRef = useRef(null);
const visualize = useCallback((stream) => {
const audioContext = new (window.AudioContext || window.webkitAudioContext)();
const source = audioContext... | transformers.js/examples/webgpu-whisper/src/components/AudioVisualizer.jsx/0 | {
"file_path": "transformers.js/examples/webgpu-whisper/src/components/AudioVisualizer.jsx",
"repo_id": "transformers.js",
"token_count": 865
} | 367 |
import { useState, forwardRef, useRef, useImperativeHandle, useEffect, useCallback } from 'react';
const EXAMPLE_URL = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/whisper-timestamps-demo.mp4';
const MediaInput = forwardRef(({ onInputChange, onTimeUpdate, ...props }, ref) => {
// UI s... | transformers.js/examples/whisper-word-timestamps/src/components/MediaInput.jsx/0 | {
"file_path": "transformers.js/examples/whisper-word-timestamps/src/components/MediaInput.jsx",
"repo_id": "transformers.js",
"token_count": 3304
} | 368 |
def generate_tokenizer_json(tokenizer):
vocab = tokenizer.get_vocab()
normalizers = []
if tokenizer.normalize:
# Lowercase the input string
normalizers.append({
"type": "Lowercase",
})
if tokenizer.language == 'ron':
# Replace diacritics
normalize... | transformers.js/scripts/extra/vits.py/0 | {
"file_path": "transformers.js/scripts/extra/vits.py",
"repo_id": "transformers.js",
"token_count": 1431
} | 369 |
/**
* @module generation/parameters
*/
/**
* @typedef {Object} GenerationFunctionParameters
* @property {import('../utils/tensor.js').Tensor} [inputs=null] (`Tensor` of varying shape depending on the modality, *optional*):
* The sequence used as a prompt for the generation or as model inputs to the encoder. If `... | transformers.js/src/generation/parameters.js/0 | {
"file_path": "transformers.js/src/generation/parameters.js",
"repo_id": "transformers.js",
"token_count": 701
} | 370 |
import {
ImageProcessor,
post_process_object_detection,
post_process_panoptic_segmentation,
post_process_instance_segmentation,
} from "../../base/image_processors_utils.js";
import { full } from '../../utils/tensor.js';
/**
* @typedef {object} DetrFeatureExtractorResultProps
* @property {import('... | transformers.js/src/models/detr/image_processing_detr.js/0 | {
"file_path": "transformers.js/src/models/detr/image_processing_detr.js",
"repo_id": "transformers.js",
"token_count": 711
} | 371 |
import {
ImageProcessor,
} from "../../base/image_processors_utils.js";
export class VLMImageProcessor extends ImageProcessor {
constructor(config) {
super({
do_pad: true,
pad_size: {
width: config.image_size,
height: config.image_size,
... | transformers.js/src/models/janus/image_processing_janus.js/0 | {
"file_path": "transformers.js/src/models/janus/image_processing_janus.js",
"repo_id": "transformers.js",
"token_count": 359
} | 372 |
import { DonutImageProcessor } from "../donut/image_processing_donut.js";
// NOTE: extends DonutImageProcessor
export class NougatImageProcessor extends DonutImageProcessor { }
| transformers.js/src/models/nougat/image_processing_nougat.js/0 | {
"file_path": "transformers.js/src/models/nougat/image_processing_nougat.js",
"repo_id": "transformers.js",
"token_count": 53
} | 373 |
import {
ImageProcessor,
post_process_semantic_segmentation,
} from "../../base/image_processors_utils.js";
export class SapiensImageProcessor extends ImageProcessor {
/** @type {typeof post_process_semantic_segmentation} */
post_process_semantic_segmentation(...args) {
return post_process_se... | transformers.js/src/models/sapiens/image_processing_sapiens.js/0 | {
"file_path": "transformers.js/src/models/sapiens/image_processing_sapiens.js",
"repo_id": "transformers.js",
"token_count": 145
} | 374 |
import { AutoTokenizer } from "../../tokenizers.js";
import { AutoFeatureExtractor } from "../auto/feature_extraction_auto.js";
import { Processor } from "../../base/processing_utils.js";
export class Wav2Vec2Processor extends Processor {
static tokenizer_class = AutoTokenizer
static feature_extractor_class = ... | transformers.js/src/models/wav2vec2/processing_wav2vec2.js/0 | {
"file_path": "transformers.js/src/models/wav2vec2/processing_wav2vec2.js",
"repo_id": "transformers.js",
"token_count": 211
} | 375 |
/**
* The list of devices supported by Transformers.js
*/
export const DEVICE_TYPES = Object.freeze({
auto: 'auto', // Auto-detect based on device and environment
gpu: 'gpu', // Auto-detect GPU
cpu: 'cpu', // CPU
wasm: 'wasm', // WebAssembly
webgpu: 'webgpu', // WebGPU
cuda: 'cuda', // CUDA
... | transformers.js/src/utils/devices.js/0 | {
"file_path": "transformers.js/src/utils/devices.js",
"repo_id": "transformers.js",
"token_count": 247
} | 376 |
import { PreTrainedTokenizer, ArceeForCausalLM } 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("ArceeForCausalLM", () => {
const model_id = "onnx-internal-testing/t... | transformers.js/tests/models/arcee/test_modeling_arcee.js/0 | {
"file_path": "transformers.js/tests/models/arcee/test_modeling_arcee.js",
"repo_id": "transformers.js",
"token_count": 792
} | 377 |
import { DacFeatureExtractor, DacModel, DacEncoderModel, DacDecoderModel } 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("DacModel", () => {
const model_id = "hf-in... | transformers.js/tests/models/dac/test_modeling_dac.js/0 | {
"file_path": "transformers.js/tests/models/dac/test_modeling_dac.js",
"repo_id": "transformers.js",
"token_count": 1194
} | 378 |
import { AutoProcessor, JinaCLIPProcessor } 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("JinaCLIPProcessor", () => {
const model_id = "jinaai/jina-... | transformers.js/tests/models/jina_clip/test_processor_jina_clip.js/0 | {
"file_path": "transformers.js/tests/models/jina_clip/test_processor_jina_clip.js",
"repo_id": "transformers.js",
"token_count": 863
} | 379 |
import { T5Tokenizer, MusicgenForConditionalGeneration, full } from "../../../src/transformers.js";
import { MAX_MODEL_LOAD_TIME, MAX_TEST_EXECUTION_TIME, MAX_MODEL_DISPOSE_TIME, DEFAULT_MODEL_OPTIONS } from "../../init.js";
export default () => {
describe("MusicgenForConditionalGeneration", () => {
const model... | transformers.js/tests/models/musicgen/test_modeling_musicgen.js/0 | {
"file_path": "transformers.js/tests/models/musicgen/test_modeling_musicgen.js",
"repo_id": "transformers.js",
"token_count": 1011
} | 380 |
import { Qwen2VLProcessor, Qwen2VLForConditionalGeneration, RawImage } from "../../../src/transformers.js";
import { MAX_MODEL_LOAD_TIME, MAX_TEST_EXECUTION_TIME, MAX_MODEL_DISPOSE_TIME, DEFAULT_MODEL_OPTIONS } from "../../init.js";
export default () => {
const CONVERSATION = [
{
role: "user",
conte... | transformers.js/tests/models/qwen2_vl/test_modeling_qwen2_vl.js/0 | {
"file_path": "transformers.js/tests/models/qwen2_vl/test_modeling_qwen2_vl.js",
"repo_id": "transformers.js",
"token_count": 1367
} | 381 |
import { AutoFeatureExtractor, WeSpeakerFeatureExtractor } from "../../../src/transformers.js";
import { MAX_FEATURE_EXTRACTOR_LOAD_TIME, MAX_TEST_EXECUTION_TIME } from "../../init.js";
export default () => {
// WeSpeakerFeatureExtractor
describe("WeSpeakerFeatureExtractor", () => {
const model_id = "onnx-com... | transformers.js/tests/models/wespeaker_resnet/test_feature_extraction_wespeaker_resnet.js/0 | {
"file_path": "transformers.js/tests/models/wespeaker_resnet/test_feature_extraction_wespeaker_resnet.js",
"repo_id": "transformers.js",
"token_count": 1014
} | 382 |
import { pipeline, ImageSegmentationPipeline } 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-segmentation";
export default ()... | transformers.js/tests/pipelines/test_pipelines_image_segmentation.js/0 | {
"file_path": "transformers.js/tests/pipelines/test_pipelines_image_segmentation.js",
"repo_id": "transformers.js",
"token_count": 1834
} | 383 |
# coding=utf-8
# Copyright 2022 The HuggingFace Inc. team.
#
# 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... | transformers/.circleci/create_circleci_config.py/0 | {
"file_path": "transformers/.circleci/create_circleci_config.py",
"repo_id": "transformers",
"token_count": 7498
} | 384 |
FROM python:3.9-slim
ENV PYTHONDONTWRITEBYTECODE=1
ARG REF=main
RUN echo ${REF}
USER root
RUN apt-get update && apt-get install -y --no-install-recommends libsndfile1-dev espeak-ng time git g++ cmake pkg-config openssh-client git git-lfs
ENV UV_PYTHON=/usr/local/bin/python
RUN pip --no-cache-dir install uv && uv pip i... | transformers/docker/torch-tf-light.dockerfile/0 | {
"file_path": "transformers/docker/torch-tf-light.dockerfile",
"repo_id": "transformers",
"token_count": 386
} | 385 |
FROM nvidia/cuda:12.1.0-cudnn8-devel-ubuntu22.04
LABEL maintainer="Hugging Face"
ARG DEBIAN_FRONTEND=noninteractive
RUN apt update
RUN apt install -y git libsndfile1-dev tesseract-ocr espeak-ng python3 python3-pip ffmpeg
RUN python3 -m pip install --no-cache-dir --upgrade pip
ARG REF=main
RUN git clone https://githu... | transformers/docker/transformers-tensorflow-gpu/Dockerfile/0 | {
"file_path": "transformers/docker/transformers-tensorflow-gpu/Dockerfile",
"repo_id": "transformers",
"token_count": 380
} | 386 |
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