text stringlengths 7 318k | id stringlengths 14 166 | metadata dict | __index_level_0__ int64 0 439 |
|---|---|---|---|
# coding=utf-8
# Copyright 2022 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... | transformers/tests/models/mask2former/test_modeling_mask2former.py/0 | {
"file_path": "transformers/tests/models/mask2former/test_modeling_mask2former.py",
"repo_id": "transformers",
"token_count": 7759
} | 357 |
# coding=utf-8
# Copyright 2022 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... | transformers/tests/models/nat/test_modeling_nat.py/0 | {
"file_path": "transformers/tests/models/nat/test_modeling_nat.py",
"repo_id": "transformers",
"token_count": 6239
} | 358 |
# coding=utf-8
# Copyright 2023 IBM and 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
#
# Unle... | transformers/tests/models/patchtsmixer/test_modeling_patchtsmixer.py/0 | {
"file_path": "transformers/tests/models/patchtsmixer/test_modeling_patchtsmixer.py",
"repo_id": "transformers",
"token_count": 20454
} | 359 |
# coding=utf-8
# Copyright 2023 Microsoft and the HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.... | transformers/tests/models/phi/test_modeling_phi.py/0 | {
"file_path": "transformers/tests/models/phi/test_modeling_phi.py",
"repo_id": "transformers",
"token_count": 9169
} | 360 |
# 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 applicabl... | transformers/tests/models/pop2piano/test_processor_pop2piano.py/0 | {
"file_path": "transformers/tests/models/pop2piano/test_processor_pop2piano.py",
"repo_id": "transformers",
"token_count": 4029
} | 361 |
# 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... | transformers/tests/models/rag/test_retrieval_rag.py/0 | {
"file_path": "transformers/tests/models/rag/test_retrieval_rag.py",
"repo_id": "transformers",
"token_count": 6761
} | 362 |
# coding=utf-8
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requir... | transformers/tests/models/rembert/test_tokenization_rembert.py/0 | {
"file_path": "transformers/tests/models/rembert/test_tokenization_rembert.py",
"repo_id": "transformers",
"token_count": 6741
} | 363 |
# coding=utf-8
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requir... | transformers/tests/models/roc_bert/test_tokenization_roc_bert.py/0 | {
"file_path": "transformers/tests/models/roc_bert/test_tokenization_roc_bert.py",
"repo_id": "transformers",
"token_count": 7464
} | 364 |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | transformers/tests/models/seamless_m4t/test_tokenization_seamless_m4t.py/0 | {
"file_path": "transformers/tests/models/seamless_m4t/test_tokenization_seamless_m4t.py",
"repo_id": "transformers",
"token_count": 15133
} | 365 |
# coding=utf-8
# Copyright 2022 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 law... | transformers/tests/models/speech_encoder_decoder/test_modeling_flax_speech_encoder_decoder.py/0 | {
"file_path": "transformers/tests/models/speech_encoder_decoder/test_modeling_flax_speech_encoder_decoder.py",
"repo_id": "transformers",
"token_count": 17887
} | 366 |
# coding=utf-8
# Copyright 2022 Google SwitchTransformers Authors and 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... | transformers/tests/models/switch_transformers/test_modeling_switch_transformers.py/0 | {
"file_path": "transformers/tests/models/switch_transformers/test_modeling_switch_transformers.py",
"repo_id": "transformers",
"token_count": 21272
} | 367 |
# coding=utf-8
# Copyright 2021 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 law... | transformers/tests/models/vision_encoder_decoder/test_modeling_flax_vision_encoder_decoder.py/0 | {
"file_path": "transformers/tests/models/vision_encoder_decoder/test_modeling_flax_vision_encoder_decoder.py",
"repo_id": "transformers",
"token_count": 9435
} | 368 |
# coding=utf-8
# Copyright 2022 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... | transformers/tests/models/vit_hybrid/test_modeling_vit_hybrid.py/0 | {
"file_path": "transformers/tests/models/vit_hybrid/test_modeling_vit_hybrid.py",
"repo_id": "transformers",
"token_count": 4621
} | 369 |
# 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... | transformers/tests/models/wav2vec2_with_lm/test_processor_wav2vec2_with_lm.py/0 | {
"file_path": "transformers/tests/models/wav2vec2_with_lm/test_processor_wav2vec2_with_lm.py",
"repo_id": "transformers",
"token_count": 8780
} | 370 |
# coding=utf-8
# 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 requir... | transformers/tests/models/xglm/test_tokenization_xglm.py/0 | {
"file_path": "transformers/tests/models/xglm/test_tokenization_xglm.py",
"repo_id": "transformers",
"token_count": 4199
} | 371 |
# 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... | transformers/tests/pipelines/test_pipelines_text2text_generation.py/0 | {
"file_path": "transformers/tests/pipelines/test_pipelines_text2text_generation.py",
"repo_id": "transformers",
"token_count": 2111
} | 372 |
# coding=utf-8
# Copyright 2022 The HuggingFace Team 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 clone of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable... | transformers/tests/quantization/bnb/test_4bit.py/0 | {
"file_path": "transformers/tests/quantization/bnb/test_4bit.py",
"repo_id": "transformers",
"token_count": 10958
} | 373 |
import argparse
import logging
import sys
import time
import tensorflow as tf
from datasets import load_dataset
from packaging.version import parse
from transformers import AutoTokenizer, TFAutoModelForSequenceClassification
try:
import tf_keras as keras
except (ModuleNotFoundError, ImportError):
import ker... | transformers/tests/sagemaker/scripts/tensorflow/run_tf.py/0 | {
"file_path": "transformers/tests/sagemaker/scripts/tensorflow/run_tf.py",
"repo_id": "transformers",
"token_count": 1577
} | 374 |
# 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... | transformers/tests/test_modeling_flax_utils.py/0 | {
"file_path": "transformers/tests/test_modeling_flax_utils.py",
"repo_id": "transformers",
"token_count": 6875
} | 375 |
# 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... | transformers/tests/tools/test_image_question_answering.py/0 | {
"file_path": "transformers/tests/tools/test_image_question_answering.py",
"repo_id": "transformers",
"token_count": 768
} | 376 |
# 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... | transformers/tests/trainer/test_trainer_tpu.py/0 | {
"file_path": "transformers/tests/trainer/test_trainer_tpu.py",
"repo_id": "transformers",
"token_count": 1651
} | 377 |
# coding=utf-8
# Copyright 2022 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... | transformers/tests/utils/test_image_processing_utils.py/0 | {
"file_path": "transformers/tests/utils/test_image_processing_utils.py",
"repo_id": "transformers",
"token_count": 1072
} | 378 |
# coding=utf-8
# Copyright 2023 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/utils/check_docstrings.py/0 | {
"file_path": "transformers/utils/check_docstrings.py",
"repo_id": "transformers",
"token_count": 16779
} | 379 |
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def extract_time_from_single_job(job):
"""Extract time info from a single job in a GitHub Actions workflow run"""
job_info = {}
start = job["started_at"]
end = job["completed_at"]
start_datetime ... | transformers/utils/get_github_job_time.py/0 | {
"file_path": "transformers/utils/get_github_job_time.py",
"repo_id": "transformers",
"token_count": 835
} | 380 |
from transformers import CLIPImageProcessor
class CustomImageProcessor(CLIPImageProcessor):
pass
| transformers/utils/test_module/custom_image_processing.py/0 | {
"file_path": "transformers/utils/test_module/custom_image_processing.py",
"repo_id": "transformers",
"token_count": 29
} | 381 |
from dataclasses import dataclass
import tyro
from huggingface_hub import HfApi
@dataclass
class Args:
folder_path: str = "benchmark/trl"
path_in_repo: str = "images/benchmark"
repo_id: str = "trl-internal-testing/example-images"
repo_type: str = "dataset"
args = tyro.cli(Args)
api = HfApi()
api.u... | trl/benchmark/upload_benchmark.py/0 | {
"file_path": "trl/benchmark/upload_benchmark.py",
"repo_id": "trl",
"token_count": 200
} | 382 |
# Learning Tools (Experimental 🧪)
Using Large Language Models (LLMs) with tools has been a popular topic recently with awesome works such as [ToolFormer](https://arxiv.org/abs/2302.04761) and [ToolBench](https://arxiv.org/pdf/2305.16504.pdf). In TRL, we provide a simple example of how to teach LLM to use tools with r... | trl/docs/source/learning_tools.mdx/0 | {
"file_path": "trl/docs/source/learning_tools.mdx",
"repo_id": "trl",
"token_count": 3876
} | 383 |
# 0. imports
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import torch
from datasets import Dataset, load_dataset
from peft import LoraConfig
from transformers import AutoModelForCausalLM, AutoTokenizer, HfArgumentParser, TrainingArguments
from trl import DPOTrainer
# Define ... | trl/examples/research_projects/stack_llama_2/scripts/dpo_llama2.py/0 | {
"file_path": "trl/examples/research_projects/stack_llama_2/scripts/dpo_llama2.py",
"repo_id": "trl",
"token_count": 3560
} | 384 |
# 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 applicabl... | trl/tests/test_dpo_trainer.py/0 | {
"file_path": "trl/tests/test_dpo_trainer.py",
"repo_id": "trl",
"token_count": 9731
} | 385 |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | trl/trl/trainer/ppo_config.py/0 | {
"file_path": "trl/trl/trainer/ppo_config.py",
"repo_id": "trl",
"token_count": 2849
} | 386 |
<!--Copyright 2022 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | accelerate/docs/source/basic_tutorials/install.md/0 | {
"file_path": "accelerate/docs/source/basic_tutorials/install.md",
"repo_id": "accelerate",
"token_count": 996
} | 0 |
<!--Copyright 2021 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | accelerate/docs/source/package_reference/accelerator.md/0 | {
"file_path": "accelerate/docs/source/package_reference/accelerator.md",
"repo_id": "accelerate",
"token_count": 2148
} | 1 |
<!--Copyright 2022 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | accelerate/docs/source/usage_guides/deepspeed.md/0 | {
"file_path": "accelerate/docs/source/usage_guides/deepspeed.md",
"repo_id": "accelerate",
"token_count": 9829
} | 2 |
# What are these scripts?
All scripts in this folder originate from the `nlp_example.py` file, as it is a very simplistic NLP training example using Accelerate with zero extra features.
From there, each further script adds in just **one** feature of Accelerate, showing how you can quickly modify your own scripts to i... | accelerate/examples/by_feature/README.md/0 | {
"file_path": "accelerate/examples/by_feature/README.md",
"repo_id": "accelerate",
"token_count": 1218
} | 3 |
{
"fp16": {
"enabled": true,
"loss_scale": 0,
"loss_scale_window": 1000,
"initial_scale_power": 16,
"hysteresis": 2,
"min_loss_scale": 1
},
"optimizer": {
"type": "AdamW",
"params": {
"lr": "auto",
"weight_decay": "auto"... | accelerate/examples/deepspeed_config_templates/zero_stage1_config.json/0 | {
"file_path": "accelerate/examples/deepspeed_config_templates/zero_stage1_config.json",
"repo_id": "accelerate",
"token_count": 614
} | 4 |
[isort]
default_section = FIRSTPARTY
ensure_newline_before_comments = True
force_grid_wrap = 0
include_trailing_comma = True
known_first_party = accelerate
line_length = 119
lines_after_imports = 2
multi_line_output = 3
use_parentheses = True
[flake8]
ignore = E203, E722, E501, E741, W503, W605
max-line-length = 119
| accelerate/setup.cfg/0 | {
"file_path": "accelerate/setup.cfg",
"repo_id": "accelerate",
"token_count": 117
} | 5 |
#!/usr/bin/env python
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unles... | accelerate/src/accelerate/commands/env.py/0 | {
"file_path": "accelerate/src/accelerate/commands/env.py",
"repo_id": "accelerate",
"token_count": 1090
} | 6 |
#!/usr/bin/env python
# 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
#
# Unles... | accelerate/src/accelerate/test_utils/scripts/test_script.py/0 | {
"file_path": "accelerate/src/accelerate/test_utils/scripts/test_script.py",
"repo_id": "accelerate",
"token_count": 11089
} | 7 |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate/src/accelerate/utils/modeling.py/0 | {
"file_path": "accelerate/src/accelerate/utils/modeling.py",
"repo_id": "accelerate",
"token_count": 32341
} | 8 |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate/tests/test_cli.py/0 | {
"file_path": "accelerate/tests/test_cli.py",
"repo_id": "accelerate",
"token_count": 6731
} | 9 |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate/tests/test_offload.py/0 | {
"file_path": "accelerate/tests/test_offload.py",
"repo_id": "accelerate",
"token_count": 2058
} | 10 |
<p align="center">
<img src="https://raw.githubusercontent.com/huggingface/alignment-handbook/main/assets/handbook.png">
</p>
<p align="center">
🤗 <a href="https://huggingface.co/collections/alignment-handbook/handbook-v01-models-and-datasets-654e424d22e6880da5ebc015" target="_blank">Models & Datasets</a> | 📃 ... | alignment-handbook/README.md/0 | {
"file_path": "alignment-handbook/README.md",
"repo_id": "alignment-handbook",
"token_count": 2053
} | 11 |
# Model arguments
model_name_or_path: alignment-handbook/zephyr-7b-sft-full
torch_dtype: null
# Data training arguments
# For definitions, see: src/h4/training/config.py
dataset_mixer:
HuggingFaceH4/ultrafeedback_binarized: 1.0
dataset_splits:
- train_prefs
- test_prefs
preprocessing_num_workers: 12
# DPOTrainer ar... | alignment-handbook/recipes/zephyr-7b-beta/dpo/config_full.yaml/0 | {
"file_path": "alignment-handbook/recipes/zephyr-7b-beta/dpo/config_full.yaml",
"repo_id": "alignment-handbook",
"token_count": 365
} | 12 |
# Model arguments
model_name_or_path: mistralai/Mistral-7B-v0.1
model_revision: main
torch_dtype: bfloat16
use_flash_attention_2: true
# Data training arguments
dataset_mixer:
HuggingFaceH4/ultrachat_200k: 1.0
dataset_splits:
- train_sft
- test_sft
preprocessing_num_workers: 12
# SFT trainer config
bf16: true
do_ev... | alignment-handbook/tests/fixtures/config_sft_full.yaml/0 | {
"file_path": "alignment-handbook/tests/fixtures/config_sft_full.yaml",
"repo_id": "alignment-handbook",
"token_count": 357
} | 13 |
[package]
name = "candle-book"
version.workspace = true
edition.workspace = true
description.workspace = true
repository.workspace = true
keywords.workspace = true
categories.workspace = true
license.workspace = true
readme = "README.md"
[dependencies]
accelerate-src = { workspace = true, optional = true }
candle = { ... | candle/candle-book/Cargo.toml/0 | {
"file_path": "candle/candle-book/Cargo.toml",
"repo_id": "candle",
"token_count": 467
} | 14 |
# Installation
**With Cuda support**:
1. First, make sure that Cuda is correctly installed.
- `nvcc --version` should print information about your Cuda compiler driver.
- `nvidia-smi --query-gpu=compute_cap --format=csv` should print your GPUs compute capability, e.g. something
like:
```bash
compute_cap
8.9
```
You... | candle/candle-book/src/guide/installation.md/0 | {
"file_path": "candle/candle-book/src/guide/installation.md",
"repo_id": "candle",
"token_count": 487
} | 15 |
mod benchmarks;
use criterion::criterion_main;
criterion_main!(
benchmarks::affine::benches,
benchmarks::matmul::benches,
benchmarks::random::benches,
benchmarks::where_cond::benches
);
| candle/candle-core/benches/bench_main.rs/0 | {
"file_path": "candle/candle-core/benches/bench_main.rs",
"repo_id": "candle",
"token_count": 71
} | 16 |
#![allow(clippy::excessive_precision)]
// Code taken from https://github.com/statrs-dev/statrs
//! Provides the [error](https://en.wikipedia.org/wiki/Error_function) and
//! related functions
mod evaluate {
//! Provides functions that don't have a numerical solution and must
//! be solved computationally (e.g.... | candle/candle-core/src/cpu/erf.rs/0 | {
"file_path": "candle/candle-core/src/cpu/erf.rs",
"repo_id": "candle",
"token_count": 11974
} | 17 |
//! ML framework for Rust
//!
//! ```rust
//! use candle_core::{Tensor, DType, Device};
//! # use candle_core::Error;
//! # fn main() -> Result<(), Error>{
//!
//! let a = Tensor::arange(0f32, 6f32, &Device::Cpu)?.reshape((2, 3))?;
//! let b = Tensor::arange(0f32, 12f32, &Device::Cpu)?.reshape((3, 4))?;
//!
//! let c =... | candle/candle-core/src/lib.rs/0 | {
"file_path": "candle/candle-core/src/lib.rs",
"repo_id": "candle",
"token_count": 1404
} | 18 |
use crate::{Result, Tensor, WithDType};
pub enum TensorScalar {
Tensor(Tensor),
Scalar(Tensor),
}
pub trait TensorOrScalar {
fn to_tensor_scalar(self) -> Result<TensorScalar>;
}
impl TensorOrScalar for &Tensor {
fn to_tensor_scalar(self) -> Result<TensorScalar> {
Ok(TensorScalar::Tensor(self.... | candle/candle-core/src/scalar.rs/0 | {
"file_path": "candle/candle-core/src/scalar.rs",
"repo_id": "candle",
"token_count": 261
} | 19 |
use candle_core::{
bail,
quantized::{self, GgmlDType},
test_device,
test_utils::to_vec2_round,
Device, Module, Result, Tensor,
};
use quantized::{k_quants, GgmlType};
use rand::prelude::*;
const GGML_TEST_SIZE: usize = 32 * 128;
const GGML_MAX_QUANTIZATION_TOTAL_ERROR: f32 = 0.002;
const GGML_MAX_... | candle/candle-core/tests/quantized_tests.rs/0 | {
"file_path": "candle/candle-core/tests/quantized_tests.rs",
"repo_id": "candle",
"token_count": 18700
} | 20 |
# candle-examples
| candle/candle-examples/README.md/0 | {
"file_path": "candle/candle-examples/README.md",
"repo_id": "candle",
"token_count": 6
} | 21 |
#[cfg(feature = "mkl")]
extern crate intel_mkl_src;
#[cfg(feature = "accelerate")]
extern crate accelerate_src;
use candle_transformers::models::distilbert::{Config, DistilBertModel, DTYPE};
use anyhow::{Error as E, Result};
use candle::{Device, Tensor};
use candle_nn::VarBuilder;
use clap::Parser;
use hf_hub::{api::... | candle/candle-examples/examples/distilbert/main.rs/0 | {
"file_path": "candle/candle-examples/examples/distilbert/main.rs",
"repo_id": "candle",
"token_count": 1939
} | 22 |
#[cfg(feature = "mkl")]
extern crate intel_mkl_src;
#[cfg(feature = "accelerate")]
extern crate accelerate_src;
use anyhow::Error as E;
use clap::{Parser, ValueEnum};
use candle::{DType, Tensor};
use candle_examples::token_output_stream::TokenOutputStream;
use candle_nn::VarBuilder;
use candle_transformers::models::... | candle/candle-examples/examples/marian-mt/main.rs/0 | {
"file_path": "candle/candle-examples/examples/marian-mt/main.rs",
"repo_id": "candle",
"token_count": 2385
} | 23 |
#[cfg(feature = "mkl")]
extern crate intel_mkl_src;
#[cfg(feature = "accelerate")]
extern crate accelerate_src;
use anyhow::{Error as E, Result};
use clap::{Parser, ValueEnum};
use candle_transformers::models::mixformer::{Config, MixFormerSequentialForCausalLM as MixFormer};
use candle_transformers::models::phi::{Co... | candle/candle-examples/examples/phi/main.rs/0 | {
"file_path": "candle/candle-examples/examples/phi/main.rs",
"repo_id": "candle",
"token_count": 8133
} | 24 |
#[cfg(feature = "mkl")]
extern crate intel_mkl_src;
#[cfg(feature = "accelerate")]
extern crate accelerate_src;
use clap::{Parser, ValueEnum};
use candle::{DType, IndexOp, D};
use candle_nn::{Module, VarBuilder};
use candle_transformers::models::repvgg;
#[derive(Clone, Copy, Debug, ValueEnum)]
enum Which {
A0,
... | candle/candle-examples/examples/repvgg/main.rs/0 | {
"file_path": "candle/candle-examples/examples/repvgg/main.rs",
"repo_id": "candle",
"token_count": 1518
} | 25 |
#[cfg(feature = "accelerate")]
extern crate accelerate_src;
#[cfg(feature = "mkl")]
extern crate intel_mkl_src;
use candle_transformers::models::stable_diffusion;
use candle_transformers::models::wuerstchen;
use anyhow::{Error as E, Result};
use candle::{DType, Device, IndexOp, Tensor};
use clap::Parser;
use tokeniz... | candle/candle-examples/examples/wuerstchen/main.rs/0 | {
"file_path": "candle/candle-examples/examples/wuerstchen/main.rs",
"repo_id": "candle",
"token_count": 6372
} | 26 |
use candle::Result;
/// This is a wrapper around a tokenizer to ensure that tokens can be returned to the user in a
/// streaming way rather than having to wait for the full decoding.
pub struct TokenOutputStream {
tokenizer: tokenizers::Tokenizer,
tokens: Vec<u32>,
prev_index: usize,
current_index: us... | candle/candle-examples/src/token_output_stream.rs/0 | {
"file_path": "candle/candle-examples/src/token_output_stream.rs",
"repo_id": "candle",
"token_count": 1295
} | 27 |
use core::ffi::{c_int, c_void};
extern "C" {
pub(crate) fn run_mha(
q_ptr: *const c_void,
k_ptr: *const c_void,
v_ptr: *const c_void,
o_ptr: *const c_void,
softmax_lse_ptr: *const c_void,
alibi_slopes_ptr: *const c_void,
cu_seqlens_q_ptr: *const i32,
... | candle/candle-flash-attn/src/ffi.rs/0 | {
"file_path": "candle/candle-flash-attn/src/ffi.rs",
"repo_id": "candle",
"token_count": 670
} | 28 |
#include "cuda_utils.cuh"
#include <cmath>
#include <stdint.h>
const int BLOCK_SIZE = 1024;
// TODO: Maybe add some fast_sum_f16_f32 variant that not only accumulate in f32
// but also expect a f32 output so that this can be used for normalization e.g.
// in softmax.
// Fast reduce sum kernel, this assumes that the ... | candle/candle-kernels/src/reduce.cu/0 | {
"file_path": "candle/candle-kernels/src/reduce.cu",
"repo_id": "candle",
"token_count": 8419
} | 29 |
use super::*;
use half::{bf16, f16};
use metal::{Buffer, Device, MTLResourceOptions};
fn read_to_vec<T: Clone>(buffer: &Buffer, n: usize) -> Vec<T> {
let ptr = buffer.contents() as *const T;
assert!(!ptr.is_null());
let slice = unsafe { std::slice::from_raw_parts(ptr, n) };
slice.to_vec()
}
fn new_buf... | candle/candle-metal-kernels/src/tests.rs/0 | {
"file_path": "candle/candle-metal-kernels/src/tests.rs",
"repo_id": "candle",
"token_count": 15462
} | 30 |
//! Group Normalization.
//!
//! This layer applies Group Normalization over a mini-batch of inputs.
use candle::{DType, Result, Tensor};
// This group norm version handles both weight and bias so removes the mean.
#[derive(Clone, Debug)]
pub struct GroupNorm {
weight: Tensor,
bias: Tensor,
eps: f64,
n... | candle/candle-nn/src/group_norm.rs/0 | {
"file_path": "candle/candle-nn/src/group_norm.rs",
"repo_id": "candle",
"token_count": 1372
} | 31 |
use candle::{Result, Shape, Tensor};
use candle_nn::encoding::one_hot;
#[test]
fn test_i64_one_hot() -> Result<()> {
let device = candle::Device::Cpu;
let indices = Tensor::new(vec![vec![0i64, 2], vec![1, -1]], &device)?;
let depth = 4;
let on_value = 1.0;
let off_value = 0.0;
let one_hot = ... | candle/candle-nn/tests/one_hot.rs/0 | {
"file_path": "candle/candle-nn/tests/one_hot.rs",
"repo_id": "candle",
"token_count": 1592
} | 32 |
fn main() {
pyo3_build_config::add_extension_module_link_args();
}
| candle/candle-pyo3/build.rs/0 | {
"file_path": "candle/candle-pyo3/build.rs",
"repo_id": "candle",
"token_count": 30
} | 33 |
import candle
from candle import Tensor
_UNSIGNED_DTYPES = set([str(candle.u8), str(candle.u32)])
def _assert_tensor_metadata(
actual: Tensor,
expected: Tensor,
check_device: bool = True,
check_dtype: bool = True,
check_layout: bool = True,
check_stride: bool = False,
):
if check_device:... | candle/candle-pyo3/py_src/candle/testing/__init__.py/0 | {
"file_path": "candle/candle-pyo3/py_src/candle/testing/__init__.py",
"repo_id": "candle",
"token_count": 854
} | 34 |
import candle
from candle import Tensor
from candle.testing import assert_equal, assert_almost_equal
import pytest
@pytest.mark.parametrize("dtype", [candle.f32, candle.f64, candle.f16, candle.u32, candle.u8, candle.i64])
def test_assert_equal_asserts_correctly(dtype: candle.DType):
a = Tensor([1, 2, 3]).to(dtype... | candle/candle-pyo3/tests/bindings/test_testing.py/0 | {
"file_path": "candle/candle-pyo3/tests/bindings/test_testing.py",
"repo_id": "candle",
"token_count": 476
} | 35 |
use candle::{DType, Device, Result, Tensor, D};
use candle_nn::{embedding, Embedding, LayerNorm, Linear, Module, VarBuilder};
const MAX_SEQ_LEN: usize = 5000;
fn linear(size1: usize, size2: usize, bias: bool, vb: VarBuilder) -> Result<Linear> {
let weight = vb.get((size2, size1), "weight")?;
let bias = if bia... | candle/candle-transformers/src/models/falcon.rs/0 | {
"file_path": "candle/candle-transformers/src/models/falcon.rs",
"repo_id": "candle",
"token_count": 8568
} | 36 |
use std::collections::HashMap;
use candle::quantized::QTensor;
use candle::quantized::{ggml_file, gguf_file};
use candle::{DType, Device, IndexOp, Result, Tensor, D};
use candle_nn::{Embedding, Module};
pub const MAX_SEQ_LEN: usize = 4096;
#[derive(Debug, Clone)]
struct RmsNorm {
inner: candle_nn::LayerNorm,
... | candle/candle-transformers/src/models/quantized_llama.rs/0 | {
"file_path": "candle/candle-transformers/src/models/quantized_llama.rs",
"repo_id": "candle",
"token_count": 11696
} | 37 |
//! Attention Based Building Blocks
use candle::{DType, IndexOp, Result, Tensor, D};
use candle_nn as nn;
use candle_nn::Module;
#[derive(Debug)]
struct GeGlu {
proj: nn::Linear,
span: tracing::Span,
}
impl GeGlu {
fn new(vs: nn::VarBuilder, dim_in: usize, dim_out: usize) -> Result<Self> {
let pro... | candle/candle-transformers/src/models/stable_diffusion/attention.rs/0 | {
"file_path": "candle/candle-transformers/src/models/stable_diffusion/attention.rs",
"repo_id": "candle",
"token_count": 9413
} | 38 |
//! VGG-16 model implementation.
//!
//! See Very Deep Convolutional Networks for Large-Scale Image Recognition
//! <https://arxiv.org/abs/1409.1556>
use candle::{ModuleT, Result, Tensor};
use candle_nn::{FuncT, VarBuilder};
// Enum representing the different VGG models
pub enum Models {
Vgg13,
Vgg16,
Vgg1... | candle/candle-transformers/src/models/vgg.rs/0 | {
"file_path": "candle/candle-transformers/src/models/vgg.rs",
"repo_id": "candle",
"token_count": 4303
} | 39 |
pub mod text_generation;
| candle/candle-transformers/src/pipelines/mod.rs/0 | {
"file_path": "candle/candle-transformers/src/pipelines/mod.rs",
"repo_id": "candle",
"token_count": 7
} | 40 |
import init, { Model } from "./build/m.js";
async function fetchArrayBuffer(url, cacheFile = true) {
if (!cacheFile) return new Uint8Array(await (await fetch(url)).arrayBuffer());
const cacheName = "blip-candle-cache";
const cache = await caches.open(cacheName);
const cachedResponse = await cache.match(url);
... | candle/candle-wasm-examples/blip/blipWorker.js/0 | {
"file_path": "candle/candle-wasm-examples/blip/blipWorker.js",
"repo_id": "candle",
"token_count": 815
} | 41 |
mod app;
pub mod model;
pub mod worker;
pub use app::App;
pub use worker::Worker;
| candle/candle-wasm-examples/llama2-c/src/lib.rs/0 | {
"file_path": "candle/candle-wasm-examples/llama2-c/src/lib.rs",
"repo_id": "candle",
"token_count": 29
} | 42 |
import init, { run_app } from './pkg/candle_wasm_example_whisper.js';
async function main() {
await init('/pkg/candle_wasm_example_whisper_bg.wasm');
run_app();
}
main()
| candle/candle-wasm-examples/whisper/main.js/0 | {
"file_path": "candle/candle-wasm-examples/whisper/main.js",
"repo_id": "candle",
"token_count": 73
} | 43 |
fn main() {
wasm_logger::init(wasm_logger::Config::new(log::Level::Trace));
console_error_panic_hook::set_once();
yew::Renderer::<candle_wasm_example_yolo::App>::new().render();
}
| candle/candle-wasm-examples/yolo/src/bin/app.rs/0 | {
"file_path": "candle/candle-wasm-examples/yolo/src/bin/app.rs",
"repo_id": "candle",
"token_count": 82
} | 44 |
MONGODB_URL=mongodb://localhost:27017/ | chat-ui/.env.ci/0 | {
"file_path": "chat-ui/.env.ci",
"repo_id": "chat-ui",
"token_count": 16
} | 45 |
import fs from "fs";
const SECRET_CONFIG = fs.existsSync(".env.SECRET_CONFIG")
? fs.readFileSync(".env.SECRET_CONFIG", "utf8")
: process.env.SECRET_CONFIG;
if (!SECRET_CONFIG) {
throw new Error(
"SECRET_CONFIG is not defined. Please provide it either in a file or as an environment variable."
);
}
// Read the c... | chat-ui/scripts/updateLocalEnv.ts/0 | {
"file_path": "chat-ui/scripts/updateLocalEnv.ts",
"repo_id": "chat-ui",
"token_count": 217
} | 46 |
<script lang="ts">
import { navigating } from "$app/stores";
import { createEventDispatcher } from "svelte";
import { browser } from "$app/environment";
import { base } from "$app/paths";
import { page } from "$app/stores";
import CarbonClose from "~icons/carbon/close";
import CarbonTextAlignJustify from "~icon... | chat-ui/src/lib/components/MobileNav.svelte/0 | {
"file_path": "chat-ui/src/lib/components/MobileNav.svelte",
"repo_id": "chat-ui",
"token_count": 692
} | 47 |
<script lang="ts">
import { createEventDispatcher } from "svelte";
import IconGear from "~icons/bi/gear-fill";
import { base } from "$app/paths";
import type { Assistant } from "$lib/types/Assistant";
export let assistant: Pick<
Assistant,
"avatar" | "name" | "modelId" | "createdByName" | "exampleInputs" | "_... | chat-ui/src/lib/components/chat/AssistantIntroduction.svelte/0 | {
"file_path": "chat-ui/src/lib/components/chat/AssistantIntroduction.svelte",
"repo_id": "chat-ui",
"token_count": 1361
} | 48 |
// Shouldn't be needed if we dove into sveltekit internals, see https://github.com/huggingface/chat-ui/pull/88#issuecomment-1523173850
import { setTimeout } from "node:timers/promises";
import { collections } from "./database";
let closed = false;
process.on("SIGINT", () => {
closed = true;
});
export let abortedGe... | chat-ui/src/lib/server/abortedGenerations.ts/0 | {
"file_path": "chat-ui/src/lib/server/abortedGenerations.ts",
"repo_id": "chat-ui",
"token_count": 267
} | 49 |
import type { Conversation } from "$lib/types/Conversation";
import { sha256 } from "$lib/utils/sha256";
import { collections } from "../database";
export async function uploadFile(file: Blob, conv: Conversation): Promise<string> {
const sha = await sha256(await file.text());
const upload = collections.bucket.openU... | chat-ui/src/lib/server/files/uploadFile.ts/0 | {
"file_path": "chat-ui/src/lib/server/files/uploadFile.ts",
"repo_id": "chat-ui",
"token_count": 244
} | 50 |
import { writable } from "svelte/store";
export interface WebSearchParameters {
useSearch: boolean;
nItems: number;
}
export const webSearchParameters = writable<WebSearchParameters>({
useSearch: false,
nItems: 5,
});
| chat-ui/src/lib/stores/webSearchParameters.ts/0 | {
"file_path": "chat-ui/src/lib/stores/webSearchParameters.ts",
"repo_id": "chat-ui",
"token_count": 68
} | 51 |
/* eslint-disable no-shadow */
export enum UrlDependency {
ConversationList = "conversation:list",
Conversation = "conversation",
}
| chat-ui/src/lib/types/UrlDependency.ts/0 | {
"file_path": "chat-ui/src/lib/types/UrlDependency.ts",
"repo_id": "chat-ui",
"token_count": 47
} | 52 |
export async function share(url: string, title: string) {
if (navigator.share) {
navigator.share({ url, title });
} else {
await navigator.clipboard.writeText(url);
}
}
| chat-ui/src/lib/utils/share.ts/0 | {
"file_path": "chat-ui/src/lib/utils/share.ts",
"repo_id": "chat-ui",
"token_count": 63
} | 53 |
import ChatThumbnail from "./ChatThumbnail.svelte";
import { collections } from "$lib/server/database";
import { error, type RequestHandler } from "@sveltejs/kit";
import { ObjectId } from "mongodb";
import type { SvelteComponent } from "svelte";
import { Resvg } from "@resvg/resvg-js";
import satori from "satori";
im... | chat-ui/src/routes/assistant/[assistantId]/thumbnail.png/+server.ts/0 | {
"file_path": "chat-ui/src/routes/assistant/[assistantId]/thumbnail.png/+server.ts",
"repo_id": "chat-ui",
"token_count": 833
} | 54 |
import { assert, it, describe, afterEach, vi, expect } from "vitest";
import type { Cookies } from "@sveltejs/kit";
import { collections } from "$lib/server/database";
import { updateUser } from "./updateUser";
import { ObjectId } from "mongodb";
import { DEFAULT_SETTINGS } from "$lib/types/Settings";
import { defaultM... | chat-ui/src/routes/login/callback/updateUser.spec.ts/0 | {
"file_path": "chat-ui/src/routes/login/callback/updateUser.spec.ts",
"repo_id": "chat-ui",
"token_count": 1408
} | 55 |
<script lang="ts">
import type { PageData, ActionData } from "./$types";
import { page } from "$app/stores";
import AssistantSettings from "$lib/components/AssistantSettings.svelte";
export let data: PageData;
export let form: ActionData;
$: assistant = data.assistants.find((el) => el._id.toString() === $page.p... | chat-ui/src/routes/settings/assistants/[assistantId]/edit/+page.svelte/0 | {
"file_path": "chat-ui/src/routes/settings/assistants/[assistantId]/edit/+page.svelte",
"repo_id": "chat-ui",
"token_count": 130
} | 56 |
{
"background_color": "#ffffff",
"name": "HuggingChat",
"short_name": "HuggingChat",
"display": "standalone",
"start_url": "/chat",
"icons": [
{
"src": "/chat/huggingchat/icon-128x128.png",
"sizes": "128x128",
"type": "image/png"
},
{
"src": "/chat/huggingchat/icon-256x256.png",
"sizes": "256... | chat-ui/static/huggingchat/manifest.json/0 | {
"file_path": "chat-ui/static/huggingchat/manifest.json",
"repo_id": "chat-ui",
"token_count": 233
} | 57 |
import json
import os
from dataclasses import dataclass
import numpy as np
import pyarrow as pa
import datasets
from utils import get_duration
SPEED_TEST_N_EXAMPLES = 100_000_000_000
SPEED_TEST_CHUNK_SIZE = 10_000
RESULTS_BASEPATH, RESULTS_FILENAME = os.path.split(__file__)
RESULTS_FILE_PATH = os.path.join(RESULTS... | datasets/benchmarks/benchmark_getitem_100B.py/0 | {
"file_path": "datasets/benchmarks/benchmark_getitem_100B.py",
"repo_id": "datasets",
"token_count": 867
} | 58 |
# Datasets 🤝 Arrow
## What is Arrow?
[Arrow](https://arrow.apache.org/) enables large amounts of data to be processed and moved quickly. It is a specific data format that stores data in a columnar memory layout. This provides several significant advantages:
* Arrow's standard format allows [zero-copy reads](https:/... | datasets/docs/source/about_arrow.md/0 | {
"file_path": "datasets/docs/source/about_arrow.md",
"repo_id": "datasets",
"token_count": 682
} | 59 |
# Depth estimation
Depth estimation datasets are used to train a model to approximate the relative distance of every pixel in an
image from the camera, also known as depth. The applications enabled by these datasets primarily lie in areas like visual machine
perception and perception in robotics. Example applications ... | datasets/docs/source/depth_estimation.mdx/0 | {
"file_path": "datasets/docs/source/depth_estimation.mdx",
"repo_id": "datasets",
"token_count": 2848
} | 60 |
# Load text data
This guide shows you how to load text datasets. To learn how to load any type of dataset, take a look at the <a class="underline decoration-sky-400 decoration-2 font-semibold" href="./loading">general loading guide</a>.
Text files are one of the most common file types for storing a dataset. By defaul... | datasets/docs/source/nlp_load.mdx/0 | {
"file_path": "datasets/docs/source/nlp_load.mdx",
"repo_id": "datasets",
"token_count": 482
} | 61 |
# Troubleshooting
This guide aims to provide you the tools and knowledge required to navigate some common issues. If the suggestions listed
in this guide do not cover your such situation, please refer to the [Asking for Help](#asking-for-help) section to learn where to
find help with your specific issue.
## Issues w... | datasets/docs/source/troubleshoot.mdx/0 | {
"file_path": "datasets/docs/source/troubleshoot.mdx",
"repo_id": "datasets",
"token_count": 1470
} | 62 |
# Metric Card for CER
## Metric description
Character error rate (CER) is a common metric of the performance of an automatic speech recognition (ASR) system. CER is similar to Word Error Rate (WER), but operates on character instead of word.
Character error rate can be computed as:
`CER = (S + D + I) / N = (S + D... | datasets/metrics/cer/README.md/0 | {
"file_path": "datasets/metrics/cer/README.md",
"repo_id": "datasets",
"token_count": 1192
} | 63 |
""" Official evaluation script for CUAD dataset. """
import argparse
import json
import re
import string
import sys
import numpy as np
IOU_THRESH = 0.5
def get_jaccard(prediction, ground_truth):
remove_tokens = [".", ",", ";", ":"]
for token in remove_tokens:
ground_truth = ground_truth.replace(t... | datasets/metrics/cuad/evaluate.py/0 | {
"file_path": "datasets/metrics/cuad/evaluate.py",
"repo_id": "datasets",
"token_count": 3035
} | 64 |
# Copyright 2021 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# 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.... | datasets/metrics/mahalanobis/mahalanobis.py/0 | {
"file_path": "datasets/metrics/mahalanobis/mahalanobis.py",
"repo_id": "datasets",
"token_count": 1363
} | 65 |
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# 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.... | datasets/metrics/precision/precision.py/0 | {
"file_path": "datasets/metrics/precision/precision.py",
"repo_id": "datasets",
"token_count": 2663
} | 66 |
""" Official evaluation script for v1.1 of the SQuAD dataset. """
import argparse
import json
import re
import string
import sys
from collections import Counter
def normalize_answer(s):
"""Lower text and remove punctuation, articles and extra whitespace."""
def remove_articles(text):
return re.sub(r... | datasets/metrics/squad/evaluate.py/0 | {
"file_path": "datasets/metrics/squad/evaluate.py",
"repo_id": "datasets",
"token_count": 1337
} | 67 |
# Metric Card for XTREME-S
## Metric Description
The XTREME-S metric aims to evaluate model performance on the Cross-lingual TRansfer Evaluation of Multilingual Encoders for Speech (XTREME-S) benchmark.
This benchmark was designed to evaluate speech representations across languages, tasks, domains and data regimes.... | datasets/metrics/xtreme_s/README.md/0 | {
"file_path": "datasets/metrics/xtreme_s/README.md",
"repo_id": "datasets",
"token_count": 2218
} | 68 |
import platform
from argparse import ArgumentParser
import fsspec
import huggingface_hub
import pandas
import pyarrow
from datasets import __version__ as version
from datasets.commands import BaseDatasetsCLICommand
def info_command_factory(_):
return EnvironmentCommand()
class EnvironmentCommand(BaseDatasetsC... | datasets/src/datasets/commands/env.py/0 | {
"file_path": "datasets/src/datasets/commands/env.py",
"repo_id": "datasets",
"token_count": 476
} | 69 |
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