repo_id stringlengths 15 89 | file_path stringlengths 27 180 | content stringlengths 1 2.23M | __index_level_0__ int64 0 0 |
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hf_public_repos/text-generation-inference/server/exllamav2_kernels/exllamav2_kernels | hf_public_repos/text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/q_gemm_kernel_gptq.cuh | #include "compat.cuh"
__forceinline__ __device__ half2 dot22_8(half2(&dq)[4], const half* a_ptr, const half2 g_result)
{
half2 result = {};
const half2* a2_ptr = (const half2*)a_ptr;
#pragma unroll
for (int i = 0; i < 4; i++) result = __hfma2(dq[i], *a2_ptr++, result);
return __hadd2(result, g_resu... | 0 |
hf_public_repos/text-generation-inference/server/exllamav2_kernels/exllamav2_kernels | hf_public_repos/text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/compat_gemm.cuh | #ifndef _compat_gemm_cuh
#define _compat_gemm_cuh
#if defined(USE_ROCM)
// For some reason this include is not present anywhere in exllama_v2 codebase, but it is required
// for symbols as hipblasHalf.
#include <hipblas/hipblas.h>
__host__ __forceinline__ hipblasStatus_t __compat_hipblasHgemm(hipblasHandle_t hand... | 0 |
hf_public_repos/text-generation-inference/server/exllamav2_kernels/exllamav2_kernels | hf_public_repos/text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/matrix_view.cuh | #ifndef _matrix_view_cuh
#define _matrix_view_cuh
#include <cuda_runtime.h>
#include <cuda_fp16.h>
#include "quant/qdq_util.cuh"
class MatrixView_half
{
public:
const half* data;
const int height;
const int width;
__device__ __forceinline__ MatrixView_half(const half* data, const int height, const i... | 0 |
hf_public_repos/text-generation-inference/server/exllamav2_kernels/exllamav2_kernels | hf_public_repos/text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/q_matrix.cu | #include "q_matrix.cuh"
#include "matrix_view.cuh"
#include "util.cuh"
#include "quant/qdq_2.cuh"
#include "quant/qdq_3.cuh"
#include "quant/qdq_4.cuh"
#include "quant/qdq_5.cuh"
#include "quant/qdq_6.cuh"
#include "quant/qdq_8.cuh"
#define BLOCK_KN_SIZE 128
#define THREADS_X 32
#define THREADS_Y 32
// Shuffle quan... | 0 |
hf_public_repos/text-generation-inference/server/exllamav2_kernels/exllamav2_kernels | hf_public_repos/text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/q_gemm.cu | #include "q_gemm.cuh"
#include "util.cuh"
#include "matrix_view.cuh"
#include "../config.h"
#include "quant/qdq_2.cuh"
#include "quant/qdq_3.cuh"
#include "quant/qdq_4.cuh"
#include "quant/qdq_5.cuh"
#include "quant/qdq_6.cuh"
#include "quant/qdq_8.cuh"
#define BLOCK_KN_SIZE 128
#define BLOCK_M_SIZE_MAX 8
#define MAX... | 0 |
hf_public_repos/text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda | hf_public_repos/text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/quant/qdq_3.cuh | #ifndef _qdq_3_cuh
#define _qdq_3_cuh
#include "qdq_util.cuh"
#include "../../config.h"
#if QMODE_3BIT == 1
// Permutation:
//
// v9997775 55333111 u8886664 44222000 (u, v lsb)
// vjjjhhhf ffdddbbb uiiiggge eecccaaa
// vtttrrrp ppnnnlll usssqqqo oommmkkk
__forceinline__ __device__ void shuffle_3bit_32
(
uin... | 0 |
hf_public_repos/text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda | hf_public_repos/text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/quant/qdq_2.cuh | #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... | 0 |
hf_public_repos/text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda | hf_public_repos/text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/quant/qdq_5.cuh | #ifndef _qdq_5_cuh
#define _qdq_5_cuh
#include "qdq_util.cuh"
#include "../../config.h"
#if QMODE_5BIT == 1
// Permutation:
//
// v5555533 33311111 u4444422 22200000 (u, v lsb)
// vbbbbb99 99977777 uaaaaa88 88866666
// vhhhhhff fffddddd ugggggee eeeccccc
// vnnnnnll llljjjjj ummmmmkk kkkiiiii
// vtttttrr rrrppp... | 0 |
hf_public_repos/text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda | hf_public_repos/text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/quant/qdq_4.cuh | #ifndef _qdq_4_cuh
#define _qdq_4_cuh
#include "qdq_util.cuh"
#include "../../config.h"
#if QMODE_4BIT == 1
// Permutation:
//
// 77775555 33331111 66664444 22220000
__forceinline__ __device__ void shuffle_4bit_8
(
uint32_t* q,
int stride
)
{
uint32_t qa = q[0];
uint32_t qb = 0;
#pragma unroll... | 0 |
hf_public_repos/text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda | hf_public_repos/text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/quant/qdq_6.cuh | #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_... | 0 |
hf_public_repos/text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda | hf_public_repos/text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/quant/qdq_util.cuh | #ifndef _qdq_util_cuh
#define _qdq_util_cuh
union half2_uint32
{
uint32_t as_uint32;
half2 as_half2;
__device__ half2_uint32(uint32_t val) : as_uint32(val) {}
__device__ half2_uint32(half2 val) : as_half2(val) {}
};
union half_uint16
{
uint16_t as_uint16;
half as_half;
__device__ half_uint... | 0 |
hf_public_repos/text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda | hf_public_repos/text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/quant/qdq_8.cuh | #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 ... | 0 |
hf_public_repos/text-generation-inference/server/exllamav2_kernels/exllamav2_kernels | hf_public_repos/text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cpp/util.h | #ifndef _util_h
#define _util_h
#define DBGS(__x) printf("%s\n", __x)
#define DBGI(__x) printf("%s: %i\n", #__x, __x)
#define DBGI2(__x, __y) printf("%s, %s: %i, %i\n", #__x, #__y, __x, __y)
#define DBGI3(__x, __y, __z) printf("%s, %s, %s: %i, %i, %i\n", #__x, #__y, #__z, __x, __y, __z)
#define DBGF(__x) printf("%s: %... | 0 |
hf_public_repos/text-generation-inference | hf_public_repos/text-generation-inference/docs/index.html | <html>
<head>
<!-- Load the latest Swagger UI code and style from npm using unpkg.com -->
<script src="https://unpkg.com/swagger-ui-dist@3/swagger-ui-bundle.js"></script>
<link rel="stylesheet" type="text/css" href="https://unpkg.com/swagger-ui-dist@3/swagger-ui.css"/>
<title>Text Ge... | 0 |
hf_public_repos/text-generation-inference | hf_public_repos/text-generation-inference/docs/openapi.json | {
"openapi": "3.0.3",
"info": {
"title": "Text Generation Inference",
"description": "Text Generation Webserver",
"contact": {
"name": "Olivier Dehaene"
},
"license": {
"name": "Apache 2.0",
"url": "https://www.apache.org/licenses/LICENSE-2.0"
},
"version": "1.2.0"
},... | 0 |
hf_public_repos/text-generation-inference/docs | hf_public_repos/text-generation-inference/docs/source/quicktour.md | # Quick Tour
The easiest way of getting started is using the official Docker container. Install Docker following [their installation instructions](https://docs.docker.com/get-docker/).
Let's say you want to deploy [Falcon-7B Instruct](https://huggingface.co/tiiuae/falcon-7b-instruct) model with TGI. Here is an exampl... | 0 |
hf_public_repos/text-generation-inference/docs | hf_public_repos/text-generation-inference/docs/source/_toctree.yml | - sections:
- local: index
title: Text Generation Inference
- local: quicktour
title: Quick Tour
- local: installation
title: Installation
- local: supported_models
title: Supported Models and Hardware
title: Getting started
- sections:
- local: basic_tutorials/consuming_tgi
title: Consu... | 0 |
hf_public_repos/text-generation-inference/docs | hf_public_repos/text-generation-inference/docs/source/index.md | # Text Generation Inference
Text Generation Inference (TGI) is a toolkit for deploying and serving Large Language Models (LLMs). TGI enables high-performance text generation for the most popular open-source LLMs, including Llama, Falcon, StarCoder, BLOOM, GPT-NeoX, and T5.
 to learn how to run TGI with Docker.**
## Install CLI
You can use TGI command-line inter... | 0 |
hf_public_repos/text-generation-inference/docs/source | hf_public_repos/text-generation-inference/docs/source/basic_tutorials/launcher.md | # Text-generation-launcher arguments
<!-- WRAP CODE BLOCKS -->
```shell
Text Generation Launcher
Usage: text-generation-launcher [OPTIONS]
Options:
```
## MODEL_ID
```shell
--model-id <MODEL_ID>
The name of the model to load. Can be a MODEL_ID as listed on <https://hf.co/models> like `gpt2` or `Open... | 0 |
hf_public_repos/text-generation-inference/docs/source | hf_public_repos/text-generation-inference/docs/source/basic_tutorials/consuming_tgi.md | # Consuming Text Generation Inference
There are many ways you can consume Text Generation Inference server in your applications. After launching, you can use the `/generate` route and make a `POST` request to get results from the server. You can also use the `/generate_stream` route if you want TGI to return a stream ... | 0 |
hf_public_repos/text-generation-inference/docs/source | hf_public_repos/text-generation-inference/docs/source/basic_tutorials/non_core_models.md | # Non-core Model Serving
TGI supports various LLM architectures (see full list [here](../supported_models)). If you wish to serve a model that is not one of the supported models, TGI will fallback to the `transformers` implementation of that model. This means you will be unable to use some of the features introduced b... | 0 |
hf_public_repos/text-generation-inference/docs/source | hf_public_repos/text-generation-inference/docs/source/basic_tutorials/using_cli.md | # Using TGI CLI
You can use TGI command-line interface (CLI) to download weights, serve and quantize models, or get information on serving parameters. To install the CLI, please refer to [the installation section](./installation#install-cli).
`text-generation-server` lets you download the model with `download-weights... | 0 |
hf_public_repos/text-generation-inference/docs/source | hf_public_repos/text-generation-inference/docs/source/basic_tutorials/preparing_model.md | # Preparing the Model
Text Generation Inference improves the model in several aspects.
## Quantization
TGI supports [bits-and-bytes](https://github.com/TimDettmers/bitsandbytes#bitsandbytes), [GPT-Q](https://arxiv.org/abs/2210.17323) and [AWQ](https://arxiv.org/abs/2306.00978) quantization. To speed up inference wi... | 0 |
hf_public_repos/text-generation-inference/docs/source | hf_public_repos/text-generation-inference/docs/source/basic_tutorials/gated_model_access.md | # Serving Private & Gated Models
If the model you wish to serve is behind gated access or the model repository on Hugging Face Hub is private, and you have access to the model, you can provide your Hugging Face Hub access token. You can generate and copy a read token from [Hugging Face Hub tokens page](https://hugging... | 0 |
hf_public_repos/text-generation-inference/docs/source | hf_public_repos/text-generation-inference/docs/source/conceptual/paged_attention.md | # PagedAttention
LLMs struggle with memory limitations during generation. In the decoding part of generation, all the attention keys and values generated for previous tokens are stored in GPU memory for reuse. This is called _KV cache_, and it may take up a large amount of memory for large models and long sequences.
... | 0 |
hf_public_repos/text-generation-inference/docs/source | hf_public_repos/text-generation-inference/docs/source/conceptual/flash_attention.md | # Flash Attention
Scaling the transformer architecture is heavily bottlenecked by the self-attention mechanism, which has quadratic time and memory complexity. Recent developments in accelerator hardware mainly focus on enhancing compute capacities and not memory and transferring data between hardware. This results in... | 0 |
hf_public_repos/text-generation-inference/docs/source | hf_public_repos/text-generation-inference/docs/source/conceptual/safetensors.md | # Safetensors
Safetensors is a model serialization format for deep learning models. It is [faster](https://huggingface.co/docs/safetensors/speed) and safer compared to other serialization formats like pickle (which is used under the hood in many deep learning libraries).
TGI depends on safetensors format mainly to e... | 0 |
hf_public_repos/text-generation-inference/docs/source | hf_public_repos/text-generation-inference/docs/source/conceptual/streaming.md | # Streaming
## What is Streaming?
Token streaming is the mode in which the server returns the tokens one by one as the model generates them. This enables showing progressive generations to the user rather than waiting for the whole generation. Streaming is an essential aspect of the end-user experience as it reduces ... | 0 |
hf_public_repos/text-generation-inference/docs/source | hf_public_repos/text-generation-inference/docs/source/conceptual/tensor_parallelism.md | # Tensor Parallelism
Tensor parallelism is a technique used to fit a large model in multiple GPUs. For example, when multiplying the input tensors with the first weight tensor, the matrix multiplication is equivalent to splitting the weight tensor column-wise, multiplying each column with the input separately, and the... | 0 |
hf_public_repos/text-generation-inference/docs/source | hf_public_repos/text-generation-inference/docs/source/conceptual/quantization.md | # Quantization
TGI offers GPTQ and bits-and-bytes quantization to quantize large language models.
## Quantization with GPTQ
GPTQ is a post-training quantization method to make the model smaller. It quantizes the layers by finding a compressed version of that weight, that will yield a minimum mean squared error like ... | 0 |
hf_public_repos/text-generation-inference | hf_public_repos/text-generation-inference/load_tests/starcoder_load.js | import {check} from 'k6';
import http from 'k6/http';
import {Trend} from 'k6/metrics';
const host = __ENV.HOST || '127.0.0.1:3000';
const totalTime = new Trend('total_time', true);
const validationTime = new Trend('validation_time', true);
const queueTime = new Trend('queue_time', true);
const inferenceTime = new Tr... | 0 |
hf_public_repos/text-generation-inference | hf_public_repos/text-generation-inference/load_tests/vllm.js | import { get_options, run } from "./common.js";
const reference_latency_ms = 22;
const host = __ENV.HOST || '127.0.0.1:8000';
const max_new_tokens = 50;
function generate_payload(gpt){
const input = gpt["conversations"][0]["value"];
return {"prompt": input, "temperature": 0.5, "ignore_eos": true}
}
export ... | 0 |
hf_public_repos/text-generation-inference | hf_public_repos/text-generation-inference/load_tests/common.js | import { check, randomSeed } from 'k6';
import http from 'k6/http';
import { Trend, Counter } from 'k6/metrics';
import { randomItem } from 'https://jslib.k6.io/k6-utils/1.2.0/index.js';
const seed = 0;
const host = __ENV.HOST || '127.0.0.1:8000';
const timePerToken = new Trend('time_per_token', true);
const throughp... | 0 |
hf_public_repos/text-generation-inference | hf_public_repos/text-generation-inference/load_tests/tgi.js | import { get_options, run } from "./common.js";
const reference_latency_ms = 30;
const host = __ENV.HOST || '127.0.0.1:8000';
const max_new_tokens = 50;
function generate_payload(gpt){
const input = gpt["conversations"][0]["value"];
return {"inputs": input, "parameters": {"max_new_tokens": max_new_tokens, "... | 0 |
hf_public_repos/text-generation-inference | hf_public_repos/text-generation-inference/router/Cargo.toml | [package]
name = "text-generation-router"
description = "Text Generation Webserver"
build = "build.rs"
version.workspace = true
edition.workspace = true
authors.workspace = true
homepage.workspace = true
[lib]
path = "src/lib.rs"
[[bin]]
name = "text-generation-router"
path = "src/main.rs"
[dependencies]
async-strea... | 0 |
hf_public_repos/text-generation-inference | hf_public_repos/text-generation-inference/router/build.rs | use std::error::Error;
use vergen::EmitBuilder;
fn main() -> Result<(), Box<dyn Error>> {
// Try to get the git sha from the local git repository
if EmitBuilder::builder()
.fail_on_error()
.git_sha(false)
.emit()
.is_err()
{
// Unable to get the git sha
if le... | 0 |
hf_public_repos/text-generation-inference | hf_public_repos/text-generation-inference/router/README.md | # Router
Also named `webserver` throughout the docs.
This router is handling most of the logic to handle the "batches" tell
when to pass new `prefill` requests and pausing `decode` requests, which ones etc...
It uses gRPC to communicate with the shards which can therefore be kept
much simpler and focus on having the... | 0 |
hf_public_repos/text-generation-inference/router | hf_public_repos/text-generation-inference/router/grpc-metadata/Cargo.toml | [package]
name = "grpc-metadata"
version = "0.1.0"
edition = "2021"
[dependencies]
opentelemetry = "^0.20"
tonic = "^0.10"
tracing = "^0.1"
tracing-opentelemetry = "^0.21"
| 0 |
hf_public_repos/text-generation-inference/router/grpc-metadata | hf_public_repos/text-generation-inference/router/grpc-metadata/src/lib.rs | //! A crate to extract and inject a OpenTelemetry context from and to a gRPC request.
//! Inspired by: https://github.com/open-telemetry/opentelemetry-rust gRPC examples
use opentelemetry::global;
use opentelemetry::propagation::{Extractor, Injector};
use tracing_opentelemetry::OpenTelemetrySpanExt;
/// Extract conte... | 0 |
hf_public_repos/text-generation-inference/router | hf_public_repos/text-generation-inference/router/client/Cargo.toml | [package]
name = "text-generation-client"
version.workspace = true
edition.workspace = true
authors.workspace = true
homepage.workspace = true
[dependencies]
futures = "^0.3"
grpc-metadata = { path = "../grpc-metadata" }
prost = "^0.12"
thiserror = "^1.0"
tokio = { version = "^1.32", features = ["sync"] }
tonic = "^0.... | 0 |
hf_public_repos/text-generation-inference/router | hf_public_repos/text-generation-inference/router/client/build.rs | use std::fs;
fn main() -> Result<(), Box<dyn std::error::Error>> {
println!("cargo:rerun-if-changed=../../proto/generate.proto");
fs::create_dir("src/pb").unwrap_or(());
let mut config = prost_build::Config::new();
config.protoc_arg("--experimental_allow_proto3_optional");
tonic_build::configure(... | 0 |
hf_public_repos/text-generation-inference/router/client | hf_public_repos/text-generation-inference/router/client/src/client.rs | /// Single shard Client
use crate::pb::generate::v1::text_generation_service_client::TextGenerationServiceClient;
use crate::pb::generate::v1::*;
use crate::Result;
use grpc_metadata::InjectTelemetryContext;
use std::cmp::min;
use tonic::transport::{Channel, Uri};
use tracing::instrument;
/// Text Generation Inference... | 0 |
hf_public_repos/text-generation-inference/router/client | hf_public_repos/text-generation-inference/router/client/src/lib.rs | //! Text Generation gRPC client library
mod client;
#[allow(clippy::derive_partial_eq_without_eq)]
mod pb;
mod sharded_client;
pub use client::Client;
pub use pb::generate::v1::HealthResponse;
pub use pb::generate::v1::InfoResponse as ShardInfo;
pub use pb::generate::v1::{
Batch, CachedBatch, FinishReason, Genera... | 0 |
hf_public_repos/text-generation-inference/router/client | hf_public_repos/text-generation-inference/router/client/src/sharded_client.rs | /// Multi shard Client
use crate::{Batch, CachedBatch, Client, Generation, HealthResponse, ShardInfo};
use crate::{ClientError, Result};
use futures::future::join_all;
use tonic::transport::Uri;
use tracing::instrument;
#[derive(Debug, Clone)]
/// Text Generation Inference gRPC multi client
pub struct ShardedClient {
... | 0 |
hf_public_repos/text-generation-inference/router | hf_public_repos/text-generation-inference/router/src/health.rs | use std::sync::atomic::{AtomicBool, Ordering};
use std::sync::Arc;
use text_generation_client::{
Batch, NextTokenChooserParameters, Request, ShardedClient, StoppingCriteriaParameters,
};
// Note: Request ids and batch ids cannot collide.
const LIVENESS_ID: u64 = u64::MAX;
const BATCH_ID: u64 = u64::MAX;
#[derive(... | 0 |
hf_public_repos/text-generation-inference/router | hf_public_repos/text-generation-inference/router/src/lib.rs | mod health;
/// Text Generation Inference Webserver
mod infer;
mod queue;
pub mod server;
mod validation;
use infer::Infer;
use queue::{Entry, Queue};
use serde::{Deserialize, Serialize};
use utoipa::ToSchema;
use validation::Validation;
/// Hub type
#[derive(Clone, Debug, Deserialize)]
pub struct HubModelInfo {
... | 0 |
hf_public_repos/text-generation-inference/router | hf_public_repos/text-generation-inference/router/src/queue.rs | use crate::infer::InferError;
use crate::infer::InferStreamResponse;
use crate::validation::ValidGenerateRequest;
use nohash_hasher::{BuildNoHashHasher, IntMap};
use std::cmp::min;
use std::collections::VecDeque;
use text_generation_client::{Batch, Request};
use tokio::sync::{mpsc, oneshot};
use tokio::time::Instant;
u... | 0 |
hf_public_repos/text-generation-inference/router | hf_public_repos/text-generation-inference/router/src/server.rs | /// HTTP Server logic
use crate::health::Health;
use crate::infer::{InferError, InferResponse, InferStreamResponse};
use crate::validation::ValidationError;
use crate::{
BestOfSequence, CompatGenerateRequest, Details, ErrorResponse, FinishReason,
GenerateParameters, GenerateRequest, GenerateResponse, HubModelIn... | 0 |
hf_public_repos/text-generation-inference/router | hf_public_repos/text-generation-inference/router/src/validation.rs | /// Payload validation logic
use crate::validation::ValidationError::{BestOfSampling, BestOfSeed, EmptyInput};
use crate::{GenerateParameters, GenerateRequest};
use rand::{thread_rng, Rng};
use text_generation_client::{NextTokenChooserParameters, StoppingCriteriaParameters};
use thiserror::Error;
use tokenizers::tokeni... | 0 |
hf_public_repos/text-generation-inference/router | hf_public_repos/text-generation-inference/router/src/main.rs | /// Text Generation Inference webserver entrypoint
use axum::http::HeaderValue;
use clap::Parser;
use opentelemetry::sdk::propagation::TraceContextPropagator;
use opentelemetry::sdk::trace;
use opentelemetry::sdk::trace::Sampler;
use opentelemetry::sdk::Resource;
use opentelemetry::{global, KeyValue};
use opentelemetry... | 0 |
hf_public_repos/text-generation-inference/router | hf_public_repos/text-generation-inference/router/src/infer.rs | /// Batching and inference logic
use crate::validation::{Validation, ValidationError};
use crate::{Entry, Queue, Token};
use crate::{GenerateRequest, PrefillToken};
use futures::future::try_join_all;
use nohash_hasher::IntMap;
use std::sync::{
atomic::{AtomicBool, Ordering},
Arc,
};
use text_generation_client::... | 0 |
hf_public_repos | hf_public_repos/transformers/CODE_OF_CONDUCT.md |
# Contributor Covenant Code of Conduct
## Our Pledge
We as members, contributors, and leaders pledge to make participation in our
community a harassment-free experience for everyone, regardless of age, body
size, visible or invisible disability, ethnicity, sex characteristics, gender
identity and expression, level o... | 0 |
hf_public_repos | hf_public_repos/transformers/conftest.py | # 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 applicabl... | 0 |
hf_public_repos | hf_public_repos/transformers/README_hd.md | <!---
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 ... | 0 |
hf_public_repos | hf_public_repos/transformers/README_ja.md | <!---
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 ... | 0 |
hf_public_repos | hf_public_repos/transformers/LICENSE | Copyright 2018- The Hugging Face team. All rights reserved.
Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
1. Definitions.
"License" ... | 0 |
hf_public_repos | hf_public_repos/transformers/Makefile | .PHONY: deps_table_update modified_only_fixup extra_style_checks quality style fixup fix-copies test test-examples
# 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
modified_only_fixup:
$(eval modified_p... | 0 |
hf_public_repos | hf_public_repos/transformers/README_pt-br.md | <!---
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 ... | 0 |
hf_public_repos | hf_public_repos/transformers/CITATION.cff | cff-version: "1.2.0"
date-released: 2020-10
message: "If you use this software, please cite it using these metadata."
title: "Transformers: State-of-the-Art Natural Language Processing"
url: "https://github.com/huggingface/transformers"
authors:
- family-names: Wolf
given-names: Thomas
- family-names: Debut
... | 0 |
hf_public_repos | hf_public_repos/transformers/README_ru.md | <!---
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 ... | 0 |
hf_public_repos | hf_public_repos/transformers/pyproject.toml | [tool.ruff]
# Never enforce `E501` (line length violations).
ignore = ["C901", "E501", "E741", "F402", "F823" ]
select = ["C", "E", "F", "I", "W"]
line-length = 119
# Ignore import violations in all `__init__.py` files.
[tool.ruff.per-file-ignores]
"__init__.py" = ["E402", "F401", "F403", "F811"]
"src/transformers/fil... | 0 |
hf_public_repos | hf_public_repos/transformers/README_zh-hant.md | <!---
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 ... | 0 |
hf_public_repos | hf_public_repos/transformers/.coveragerc | [run]
source=transformers
omit =
# skip convertion scripts from testing for now
*/convert_*
*/__main__.py
[report]
exclude_lines =
pragma: no cover
raise
except
register_parameter | 0 |
hf_public_repos | hf_public_repos/transformers/README_ko.md | <!---
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 ... | 0 |
hf_public_repos | hf_public_repos/transformers/README.md | <!---
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 ... | 0 |
hf_public_repos | hf_public_repos/transformers/README_es.md | <!---
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 ... | 0 |
hf_public_repos | hf_public_repos/transformers/setup.py | # 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 applicabl... | 0 |
hf_public_repos | hf_public_repos/transformers/README_zh-hans.md | <!---
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 ... | 0 |
hf_public_repos | hf_public_repos/transformers/CONTRIBUTING.md | <!---
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 ... | 0 |
hf_public_repos | hf_public_repos/transformers/ISSUES.md | <!---
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 ... | 0 |
hf_public_repos | hf_public_repos/transformers/awesome-transformers.md | # Awesome projects built with Transformers
This page lists awesome projects built on top of Transformers. Transformers is more than a toolkit to use pretrained
models: it's a community of projects built around it and the Hugging Face Hub. We want Transformers to enable
developers, researchers, students, professors, en... | 0 |
hf_public_repos | hf_public_repos/transformers/hubconf.py | # 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 applicabl... | 0 |
hf_public_repos | hf_public_repos/transformers/README_te.md | <!---
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 ... | 0 |
hf_public_repos | hf_public_repos/transformers/SECURITY.md | # Security Policy
## Reporting a Vulnerability
🤗 We have our bug bounty program set up with HackerOne. Please feel free to submit vulnerability reports to our private program at https://hackerone.com/hugging_face.
Note that you'll need to be invited to our program, so send us a quick email at security@huggingface.co... | 0 |
hf_public_repos/transformers/docker | hf_public_repos/transformers/docker/transformers-doc-builder/Dockerfile | FROM python:3.8
LABEL maintainer="Hugging Face"
RUN apt update
RUN git clone https://github.com/huggingface/transformers
RUN python3 -m pip install --no-cache-dir --upgrade pip && python3 -m pip install --no-cache-dir git+https://github.com/huggingface/doc-builder ./transformers[dev]
RUN apt-get -y update && apt-get ... | 0 |
hf_public_repos/transformers/docker | hf_public_repos/transformers/docker/transformers-cpu/Dockerfile | FROM ubuntu:18.04
LABEL maintainer="Hugging Face"
LABEL repository="transformers"
RUN apt update && \
apt install -y bash \
build-essential \
git \
curl \
ca-certificates \
python3 \
python3-pip && \
... | 0 |
hf_public_repos/transformers/docker | hf_public_repos/transformers/docker/transformers-gpu/Dockerfile | FROM nvidia/cuda:10.2-cudnn7-devel-ubuntu18.04
LABEL maintainer="Hugging Face"
LABEL repository="transformers"
RUN apt update && \
apt install -y bash \
build-essential \
git \
curl \
ca-certificates \
python3 \
... | 0 |
hf_public_repos/transformers/docker | hf_public_repos/transformers/docker/transformers-all-latest-gpu/Dockerfile | FROM nvidia/cuda:11.8.0-cudnn8-devel-ubuntu20.04
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 explicit... | 0 |
hf_public_repos/transformers/docker | hf_public_repos/transformers/docker/transformers-pytorch-tpu/Dockerfile | FROM google/cloud-sdk:slim
# Build args.
ARG GITHUB_REF=refs/heads/main
# TODO: This Dockerfile installs pytorch/xla 3.6 wheels. There are also 3.7
# wheels available; see below.
ENV PYTHON_VERSION=3.6
RUN apt-get update && apt-get install -y --no-install-recommends \
build-essential \
cmake \
... | 0 |
hf_public_repos/transformers/docker | hf_public_repos/transformers/docker/transformers-pytorch-tpu/bert-base-cased.jsonnet | local base = import 'templates/base.libsonnet';
local tpus = import 'templates/tpus.libsonnet';
local utils = import "templates/utils.libsonnet";
local volumes = import "templates/volumes.libsonnet";
local bertBaseCased = base.BaseTest {
frameworkPrefix: "hf",
modelName: "bert-base-cased",
mode: "example",
con... | 0 |
hf_public_repos/transformers/docker | hf_public_repos/transformers/docker/transformers-pytorch-tpu/docker-entrypoint.sh | #!/bin/bash
source ~/.bashrc
echo "running docker-entrypoint.sh"
conda activate container
echo $KUBE_GOOGLE_CLOUD_TPU_ENDPOINTS
echo "printed TPU info"
export XRT_TPU_CONFIG="tpu_worker;0;${KUBE_GOOGLE_CLOUD_TPU_ENDPOINTS:7}"
exec "$@"#!/bin/bash
| 0 |
hf_public_repos/transformers/docker | hf_public_repos/transformers/docker/transformers-pytorch-tpu/dataset.yaml | apiVersion: v1
kind: PersistentVolume
metadata:
name: huggingface-cluster-disk
spec:
storageClassName: ""
capacity:
storage: 500Gi
accessModes:
- ReadOnlyMany
claimRef:
namespace: default
name: huggingface-cluster-disk-claim
gcePersistentDisk:
pdName: huggingface-cluster-disk
fsType:... | 0 |
hf_public_repos/transformers/docker | hf_public_repos/transformers/docker/transformers-past-gpu/Dockerfile | 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... | 0 |
hf_public_repos/transformers/docker | hf_public_repos/transformers/docker/transformers-pytorch-amd-gpu/Dockerfile | FROM rocm/dev-ubuntu-20.04:5.6
# rocm/pytorch has no version with 2.1.0
LABEL maintainer="Hugging Face"
ARG DEBIAN_FRONTEND=noninteractive
ARG PYTORCH='2.1.0'
ARG TORCH_VISION='0.16.0'
ARG TORCH_AUDIO='2.1.0'
ARG ROCM='5.6'
RUN apt update && \
apt install -y --no-install-recommends git libsndfile1-dev tesseract-... | 0 |
hf_public_repos/transformers/docker | hf_public_repos/transformers/docker/transformers-pytorch-deepspeed-latest-gpu/Dockerfile | # https://docs.nvidia.com/deeplearning/frameworks/pytorch-release-notes/rel-23-11.html#rel-23-11
FROM nvcr.io/nvidia/pytorch:23.11-py3
LABEL maintainer="Hugging Face"
ARG DEBIAN_FRONTEND=noninteractive
ARG PYTORCH='2.1.0'
# Example: `cu102`, `cu113`, etc.
ARG CUDA='cu121'
RUN apt -y update
RUN apt install -y libaio-... | 0 |
hf_public_repos/transformers/docker | hf_public_repos/transformers/docker/transformers-tensorflow-cpu/Dockerfile | FROM ubuntu:18.04
LABEL maintainer="Hugging Face"
LABEL repository="transformers"
RUN apt update && \
apt install -y bash \
build-essential \
git \
curl \
ca-certificates \
python3 \
python3-pip && \
... | 0 |
hf_public_repos/transformers/docker | hf_public_repos/transformers/docker/transformers-tensorflow-gpu/Dockerfile | FROM nvidia/cuda:11.8.0-cudnn8-devel-ubuntu20.04
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... | 0 |
hf_public_repos/transformers/docker | hf_public_repos/transformers/docker/transformers-pytorch-deepspeed-nightly-gpu/Dockerfile | # https://docs.nvidia.com/deeplearning/frameworks/pytorch-release-notes/rel-23-11.html#rel-23-11
FROM nvcr.io/nvidia/pytorch:23.11-py3
LABEL maintainer="Hugging Face"
ARG DEBIAN_FRONTEND=noninteractive
# Example: `cu102`, `cu113`, etc.
ARG CUDA='cu121'
RUN apt -y update
RUN apt install -y libaio-dev
RUN python3 -m p... | 0 |
hf_public_repos/transformers/docker | hf_public_repos/transformers/docker/transformers-pytorch-cpu/Dockerfile | FROM ubuntu:18.04
LABEL maintainer="Hugging Face"
LABEL repository="transformers"
RUN apt update && \
apt install -y bash \
build-essential \
git \
curl \
ca-certificates \
python3 \
python3-pip && \
... | 0 |
hf_public_repos/transformers/docker | hf_public_repos/transformers/docker/transformers-pytorch-gpu/Dockerfile | FROM nvidia/cuda:12.1.0-cudnn8-devel-ubuntu20.04
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... | 0 |
hf_public_repos/transformers | hf_public_repos/transformers/tests/test_tokenization_common.py | # coding=utf-8
# Copyright 2019 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... | 0 |
hf_public_repos/transformers | hf_public_repos/transformers/tests/test_modeling_common.py | # coding=utf-8
# Copyright 2019 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... | 0 |
hf_public_repos/transformers | hf_public_repos/transformers/tests/test_configuration_common.py | # coding=utf-8
# Copyright 2019 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... | 0 |
hf_public_repos/transformers | hf_public_repos/transformers/tests/test_backbone_common.py | # coding=utf-8
# Copyright 2023 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... | 0 |
hf_public_repos/transformers | hf_public_repos/transformers/tests/test_image_processing_common.py | # coding=utf-8
# Copyright 2023 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... | 0 |
hf_public_repos/transformers | hf_public_repos/transformers/tests/test_configuration_utils.py | # coding=utf-8
# Copyright 2019 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... | 0 |
hf_public_repos/transformers | hf_public_repos/transformers/tests/test_feature_extraction_common.py | # coding=utf-8
# Copyright 2021 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... | 0 |
hf_public_repos/transformers | hf_public_repos/transformers/tests/test_modeling_flax_utils.py | # 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 applicabl... | 0 |
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