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# Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | transformers/tests/trainer/test_trainer_distributed.py/0 | {
"file_path": "transformers/tests/trainer/test_trainer_distributed.py",
"repo_id": "transformers",
"token_count": 4112
} | 406 |
# 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/utils/test_hf_argparser.py/0 | {
"file_path": "transformers/tests/utils/test_hf_argparser.py",
"repo_id": "transformers",
"token_count": 6348
} | 407 |
# coding=utf-8
# Copyright 2020 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_copies.py/0 | {
"file_path": "transformers/utils/check_copies.py",
"repo_id": "transformers",
"token_count": 22136
} | 408 |
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
logger = logging.get_logger(__name__)
def extract_warnings_from_single_artifact(artifact_path, targets):
"""Extract warnings from a downl... | transformers/utils/extract_warnings.py/0 | {
"file_path": "transformers/utils/extract_warnings.py",
"repo_id": "transformers",
"token_count": 2110
} | 409 |
from transformers import PretrainedConfig
class CustomConfig(PretrainedConfig):
model_type = "custom"
def __init__(self, attribute=1, **kwargs):
self.attribute = attribute
super().__init__(**kwargs)
class NoSuperInitConfig(PretrainedConfig):
model_type = "custom"
def __init__(self,... | transformers/utils/test_module/custom_configuration.py/0 | {
"file_path": "transformers/utils/test_module/custom_configuration.py",
"repo_id": "transformers",
"token_count": 136
} | 410 |
import json
import os
from ghapi.all import GhApi
FOLDER_STRING = os.environ.get("FOLDER_STRING", "")
folder = f"benchmark/trl/{FOLDER_STRING}"
host_url = f"https://huggingface.co/datasets/trl-internal-testing/example-images/resolve/main/images/benchmark/{FOLDER_STRING}"
# Create a GitHub API instance
github_contex... | trl/benchmark/post_github_comment.py/0 | {
"file_path": "trl/benchmark/post_github_comment.py",
"repo_id": "trl",
"token_count": 358
} | 411 |
# Examples
## Introduction
The examples should work in any of the following settings (with the same script):
- single GPU
- multi GPUS (using PyTorch distributed mode)
- multi GPUS (using DeepSpeed ZeRO-Offload stages 1, 2, & 3)
- fp16 (mixed-precision), fp32 (normal precision), or bf16 (bfloat16 precisi... | trl/docs/source/example_overview.md/0 | {
"file_path": "trl/docs/source/example_overview.md",
"repo_id": "trl",
"token_count": 1969
} | 412 |
# Text Environments
Text environments provide a learning ground for language agents. It allows a language model to use tools to accomplish a task such as using a Python interpreter to answer math questions or using a search index for trivia questions. Having access to tools allows language models to solve tasks that w... | trl/docs/source/text_environments.md/0 | {
"file_path": "trl/docs/source/text_environments.md",
"repo_id": "trl",
"token_count": 2826
} | 413 |
<jupyter_start><jupyter_text>**Best-of-n sampling as an alternative to RLHF**This notebook compares reward-model scores of prompt based responses from 1. a base model (`gpt2-imdb`)2. `RLHF` tuned model based on this base-model 3. the base-model again from which we sample n responses to each prompt, score them and take ... | trl/examples/notebooks/best_of_n.ipynb/0 | {
"file_path": "trl/examples/notebooks/best_of_n.ipynb",
"repo_id": "trl",
"token_count": 1717
} | 414 |
# De-detoxifying language models
To run this code, do the following:
```shell
ACCELERATE_LOG_LEVEL=info accelerate launch --config_file {CONFIG} examples/research_projects/toxicity/scripts/gpt-j-6b-toxicity.py --log_with wandb
```
| trl/examples/research_projects/toxicity/README.md/0 | {
"file_path": "trl/examples/research_projects/toxicity/README.md",
"repo_id": "trl",
"token_count": 79
} | 415 |
# 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_environments.py/0 | {
"file_path": "trl/tests/test_environments.py",
"repo_id": "trl",
"token_count": 4813
} | 416 |
# flake8: noqa
from typing import TYPE_CHECKING
from ..import_utils import _LazyModule
_import_structure = {
"base_environment": ["TextEnvironment", "TextHistory"],
}
if TYPE_CHECKING:
from .base_environment import TextEnvironment, TextHistory
else:
import sys
sys.modules[__name__] = _LazyModule(__na... | trl/trl/environment/__init__.py/0 | {
"file_path": "trl/trl/environment/__init__.py",
"repo_id": "trl",
"token_count": 131
} | 417 |
# DPO Authors: Rafael Rafailov, Archit Sharma, Eric Mitchell, Stefano Ermon, Christopher D. Manning, and Chelsea Finn 2023
# 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.
# ... | trl/trl/trainer/dpo_trainer.py/0 | {
"file_path": "trl/trl/trainer/dpo_trainer.py",
"repo_id": "trl",
"token_count": 27951
} | 418 |
# Builds GPU docker image of PyTorch specifically
# Uses multi-staged approach to reduce size
# Stage 1
# Use base conda image to reduce time
FROM continuumio/miniconda3:latest AS compile-image
# Specify py version
ENV PYTHON_VERSION=3.9
# Install apt libs
RUN apt-get update && \
apt-get install -y curl git wget &&... | accelerate/docker/accelerate-gpu/Dockerfile/0 | {
"file_path": "accelerate/docker/accelerate-gpu/Dockerfile",
"repo_id": "accelerate",
"token_count": 539
} | 0 |
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | accelerate/docs/source/concept_guides/low_precision_training.md/0 | {
"file_path": "accelerate/docs/source/concept_guides/low_precision_training.md",
"repo_id": "accelerate",
"token_count": 1466
} | 1 |
<!--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/state.md/0 | {
"file_path": "accelerate/docs/source/package_reference/state.md",
"repo_id": "accelerate",
"token_count": 291
} | 2 |
<!--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/model_size_estimator.md/0 | {
"file_path": "accelerate/docs/source/usage_guides/model_size_estimator.md",
"repo_id": "accelerate",
"token_count": 2030
} | 3 |
# 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/big_modeling.py/0 | {
"file_path": "accelerate/src/accelerate/big_modeling.py",
"repo_id": "accelerate",
"token_count": 11237
} | 4 |
# Copyright 2022 The HuggingFace Team and Brian Chao. 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... | accelerate/src/accelerate/commands/menu/cursor.py/0 | {
"file_path": "accelerate/src/accelerate/commands/menu/cursor.py",
"repo_id": "accelerate",
"token_count": 763
} | 5 |
# 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/scheduler.py/0 | {
"file_path": "accelerate/src/accelerate/scheduler.py",
"repo_id": "accelerate",
"token_count": 1577
} | 6 |
# 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/test_utils/scripts/test_sync.py/0 | {
"file_path": "accelerate/src/accelerate/test_utils/scripts/test_sync.py",
"repo_id": "accelerate",
"token_count": 7772
} | 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/offload.py/0 | {
"file_path": "accelerate/src/accelerate/utils/offload.py",
"repo_id": "accelerate",
"token_count": 3177
} | 8 |
compute_environment: LOCAL_MACHINE
deepspeed_config: {}
distributed_type: 'NO'
fsdp_config: {}
machine_rank: 0
main_process_ip: null
main_process_port: null
main_training_function: main
mixed_precision: 'no'
num_machines: 1
num_processes: 1
use_cpu: false | accelerate/tests/test_configs/0_11_0.yaml/0 | {
"file_path": "accelerate/tests/test_configs/0_11_0.yaml",
"repo_id": "accelerate",
"token_count": 95
} | 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": 1981
} | 10 |
.PHONY: style quality
# make sure to test the local checkout in scripts and not the pre-installed one (don't use quotes!)
export PYTHONPATH = src
check_dirs := src tests scripts
style:
black --line-length 119 --target-version py310 $(check_dirs) setup.py
isort $(check_dirs) setup.py
quality:
black --check --line... | alignment-handbook/Makefile/0 | {
"file_path": "alignment-handbook/Makefile",
"repo_id": "alignment-handbook",
"token_count": 363
} | 11 |
# Comparing Preference Alignment Algorithms
This directory contains various comparisons for three algorithms: DPO, IPO, and KTO. Each algorithm has been run in different hyperparameter configurations to study their performance. Two different models and datasets have been used to compare the performance of each algorith... | alignment-handbook/recipes/pref_align_scan/README.md/0 | {
"file_path": "alignment-handbook/recipes/pref_align_scan/README.md",
"repo_id": "alignment-handbook",
"token_count": 690
} | 12 |
#!/usr/bin/env python
# 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/LI... | alignment-handbook/scripts/run_cpt.py/0 | {
"file_path": "alignment-handbook/scripts/run_cpt.py",
"repo_id": "alignment-handbook",
"token_count": 2700
} | 13 |
# coding=utf-8
# Copyright 2024 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requir... | alignment-handbook/tests/test_decontaminate.py/0 | {
"file_path": "alignment-handbook/tests/test_decontaminate.py",
"repo_id": "alignment-handbook",
"token_count": 926
} | 14 |
[book]
authors = ["Nicolas Patry"]
language = "en"
multilingual = false
src = "src"
title = "Candle Documentation"
| candle/candle-book/book.toml/0 | {
"file_path": "candle/candle-book/book.toml",
"repo_id": "candle",
"token_count": 38
} | 15 |
# Advanced Cuda usage
| candle/candle-book/src/inference/cuda/README.md/0 | {
"file_path": "candle/candle-book/src/inference/cuda/README.md",
"repo_id": "candle",
"token_count": 6
} | 16 |
use crate::benchmarks::{BenchDevice, BenchDeviceHandler};
use candle_core::{DType, Device, Tensor};
use criterion::{black_box, criterion_group, Criterion, Throughput};
use std::time::Instant;
fn run(a: &Tensor) {
a.affine(12.34, 56.78).unwrap();
}
fn run_affine_benchmark(c: &mut Criterion, device: &Device, dtype:... | candle/candle-core/benches/benchmarks/affine.rs/0 | {
"file_path": "candle/candle-core/benches/benchmarks/affine.rs",
"repo_id": "candle",
"token_count": 591
} | 17 |
pub trait VecOps: num_traits::NumAssign + Copy {
fn min(self, rhs: Self) -> Self;
fn max(self, rhs: Self) -> Self;
/// Dot-product of two vectors.
///
/// # Safety
///
/// The length of `lhs` and `rhs` have to be at least `len`. `res` has to point to a valid
/// element.
#[inline(al... | candle/candle-core/src/cpu/kernels.rs/0 | {
"file_path": "candle/candle-core/src/cpu/kernels.rs",
"repo_id": "candle",
"token_count": 2328
} | 18 |
use crate::backend::{BackendDevice, BackendStorage};
use crate::conv::{ParamsConv1D, ParamsConv2D, ParamsConvTranspose1D, ParamsConvTranspose2D};
use crate::op::{BinaryOpT, CmpOp, ReduceOp, UnaryOpT};
use crate::{CpuStorage, DType, Layout, Result, Shape};
use candle_metal_kernels;
use candle_metal_kernels::Kernels;
use... | candle/candle-core/src/metal_backend.rs/0 | {
"file_path": "candle/candle-core/src/metal_backend.rs",
"repo_id": "candle",
"token_count": 42597
} | 19 |
use crate::Result;
pub(super) fn nearest_int(v: f32) -> i32 {
v.round() as i32
}
/// Validates that the input and output are the right size and returns an iterator which maps each
/// input region `xs` to its corresponding output block in `ys`. Each output region is guaranteed
/// to be `T::BLCK_SIZE` long.
pub(s... | candle/candle-core/src/quantized/utils.rs/0 | {
"file_path": "candle/candle-core/src/quantized/utils.rs",
"repo_id": "candle",
"token_count": 5775
} | 20 |
use anyhow::Result;
use candle_core::{Device, IndexOp, Tensor};
#[test]
fn integer_index() -> Result<()> {
let dev = Device::Cpu;
let tensor = Tensor::arange(0u32, 2 * 3, &dev)?.reshape((2, 3))?;
let result = tensor.i(1)?;
assert_eq!(result.dims(), &[3]);
assert_eq!(result.to_vec1::<u32>()?, &[3, ... | candle/candle-core/tests/indexing_tests.rs/0 | {
"file_path": "candle/candle-core/tests/indexing_tests.rs",
"repo_id": "candle",
"token_count": 1994
} | 21 |
use hf_hub::{
api::sync::{Api, ApiRepo},
Repo, RepoType,
};
use parquet::file::reader::SerializedFileReader;
use std::fs::File;
#[derive(thiserror::Error, Debug)]
pub enum Error {
#[error("ApiError : {0}")]
ApiError(#[from] hf_hub::api::sync::ApiError),
#[error("IoError : {0}")]
IoError(#[from... | candle/candle-datasets/src/hub.rs/0 | {
"file_path": "candle/candle-datasets/src/hub.rs",
"repo_id": "candle",
"token_count": 900
} | 22 |
#[cfg(feature = "mkl")]
extern crate intel_mkl_src;
#[cfg(feature = "accelerate")]
extern crate accelerate_src;
use anyhow::{Error as E, Result};
use clap::Parser;
use candle_transformers::models::chatglm::{Config, Model};
use candle::{DType, Device, Tensor};
use candle_nn::VarBuilder;
use candle_transformers::gene... | candle/candle-examples/examples/chatglm/main.rs/0 | {
"file_path": "candle/candle-examples/examples/chatglm/main.rs",
"repo_id": "candle",
"token_count": 3423
} | 23 |
#![allow(unused)]
use anyhow::{Context, Result};
use std::sync::{Arc, Mutex};
pub const SAMPLE_RATE: usize = 24_000;
pub(crate) struct AudioOutputData_ {
resampled_data: std::collections::VecDeque<f32>,
resampler: rubato::FastFixedIn<f32>,
output_buffer: Vec<f32>,
input_buffer: Vec<f32>,
input_len... | candle/candle-examples/examples/encodec/audio_io.rs/0 | {
"file_path": "candle/candle-examples/examples/encodec/audio_io.rs",
"repo_id": "candle",
"token_count": 4805
} | 24 |
/// This follows the lines of:
/// https://github.com/johnma2006/mamba-minimal/blob/master/model.py
/// Simple, minimal implementation of Mamba in one file of PyTorch.
use candle::{IndexOp, Module, Result, Tensor, D};
use candle_nn::{RmsNorm, VarBuilder};
use candle_transformers::models::with_tracing::{linear, linear_... | candle/candle-examples/examples/mamba-minimal/model.rs/0 | {
"file_path": "candle/candle-examples/examples/mamba-minimal/model.rs",
"repo_id": "candle",
"token_count": 3488
} | 25 |
use candle::{DType, Device, Result, Tensor, D};
use candle_nn::{
embedding, layer_norm, linear_no_bias, Activation, Embedding, LayerNorm, Linear, Module,
VarBuilder,
};
use candle_transformers::models::{encodec, t5};
// https://github.com/huggingface/transformers/blob/cd4584e3c809bb9e1392ccd3fe38b40daba5519a/s... | candle/candle-examples/examples/musicgen/musicgen_model.rs/0 | {
"file_path": "candle/candle-examples/examples/musicgen/musicgen_model.rs",
"repo_id": "candle",
"token_count": 7592
} | 26 |
#![allow(unused)]
//! Wrappers around the Python API of Gymnasium (the new version of OpenAI gym)
use candle::{Device, Result, Tensor};
use pyo3::prelude::*;
use pyo3::types::PyDict;
/// The return value for a step.
#[derive(Debug)]
pub struct Step<A> {
pub state: Tensor,
pub action: A,
pub reward: f64,
... | candle/candle-examples/examples/reinforcement-learning/gym_env.rs/0 | {
"file_path": "candle/candle-examples/examples/reinforcement-learning/gym_env.rs",
"repo_id": "candle",
"token_count": 1716
} | 27 |
# candle-segment-anything: Segment-Anything Model
This example is based on Meta AI [Segment-Anything
Model](https://github.com/facebookresearch/segment-anything). This model
provides a robust and fast image segmentation pipeline that can be tweaked via
some prompting (requesting some points to be in the target mask, r... | candle/candle-examples/examples/segment-anything/README.md/0 | {
"file_path": "candle/candle-examples/examples/segment-anything/README.md",
"repo_id": "candle",
"token_count": 573
} | 28 |
#[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/trocr/main.rs/0 | {
"file_path": "candle/candle-examples/examples/trocr/main.rs",
"repo_id": "candle",
"token_count": 2160
} | 29 |
pub const NAMES: [&str; 80] = [
"person",
"bicycle",
"car",
"motorbike",
"aeroplane",
"bus",
"train",
"truck",
"boat",
"traffic light",
"fire hydrant",
"stop sign",
"parking meter",
"bench",
"bird",
"cat",
"dog",
"horse",
"sheep",
"cow",
... | candle/candle-examples/src/coco_classes.rs/0 | {
"file_path": "candle/candle-examples/src/coco_classes.rs",
"repo_id": "candle",
"token_count": 648
} | 30 |
// Pytorch also has an implementation of Philox RNG: https://github.com/pytorch/pytorch/blob/8ca3c881db3e3510fcb7725389f6a0633c9b992c/torch/csrc/jit/tensorexpr/cuda_random.h
#pragma once
// Philox CUDA.
namespace flash {
struct ull2 {
unsigned long long x;
unsigned long long y;
};
inline __device__ uint2 mul... | candle/candle-flash-attn/kernels/philox.cuh/0 | {
"file_path": "candle/candle-flash-attn/kernels/philox.cuh",
"repo_id": "candle",
"token_count": 2511
} | 31 |
#include "compatibility.cuh"
#include<stdint.h>
#include<cmath>
// TODO: This is often used to check that the data is contiguous so that
// kernels can be easily mapped. However this only returns true for row
// major, if all the inputs are column major, we could apply the fast path
// too (but we wouldn't if some of ... | candle/candle-kernels/src/cuda_utils.cuh/0 | {
"file_path": "candle/candle-kernels/src/cuda_utils.cuh",
"repo_id": "candle",
"token_count": 3936
} | 32 |
//! Batch Normalization.
//!
//! This layer applies Batch Normalization over a mini-batch of inputs as described in [`Batch
//! Normalization`]. The input is expected to have at least three dimensions.
//!
//! Note that this implementation is for inference only, there is no possibility to track the
//! running stats.
/... | candle/candle-nn/src/batch_norm.rs/0 | {
"file_path": "candle/candle-nn/src/batch_norm.rs",
"repo_id": "candle",
"token_count": 5325
} | 33 |
use candle::{DType, Device, Result, Shape, Tensor, Var};
use std::collections::HashMap;
use std::sync::{Arc, Mutex};
/// A `VarMap` is a store that holds named variables. Variables can be retrieved from the stores
/// and new variables can be added by providing some initialization config in case they are
/// missing.
... | candle/candle-nn/src/var_map.rs/0 | {
"file_path": "candle/candle-nn/src/var_map.rs",
"repo_id": "candle",
"token_count": 1973
} | 34 |
from candle import Tensor, QTensor, DType
from typing import (
Dict,
Tuple,
Any,
Optional,
Union,
Iterator,
Set,
overload,
Mapping,
TypeVar,
List,
)
from collections import OrderedDict, namedtuple
TensorLike = Union[Tensor, QTensor]
T = TypeVar("T", bound="Module")
class _... | candle/candle-pyo3/py_src/candle/nn/module.py/0 | {
"file_path": "candle/candle-pyo3/py_src/candle/nn/module.py",
"repo_id": "candle",
"token_count": 12028
} | 35 |
import candle
print(f"mkl: {candle.utils.has_mkl()}")
print(f"accelerate: {candle.utils.has_accelerate()}")
print(f"num-threads: {candle.utils.get_num_threads()}")
print(f"cuda: {candle.utils.cuda_is_available()}")
t = candle.Tensor(42.0)
print(t)
print(t.shape, t.rank, t.device)
print(t + t)
t = can... | candle/candle-pyo3/test.py/0 | {
"file_path": "candle/candle-pyo3/test.py",
"repo_id": "candle",
"token_count": 340
} | 36 |
use super::with_tracing::{linear, Embedding, Linear};
use candle::{Result, Tensor};
use candle_nn::{layer_norm, LayerNorm, VarBuilder};
#[derive(Debug, Clone)]
pub struct Config {
pub vocab_size: usize,
pub decoder_vocab_size: Option<usize>,
pub max_position_embeddings: usize,
pub encoder_layers: usize... | candle/candle-transformers/src/models/marian.rs/0 | {
"file_path": "candle/candle-transformers/src/models/marian.rs",
"repo_id": "candle",
"token_count": 8917
} | 37 |
use crate::quantized_nn::{layer_norm, linear, Linear};
pub use crate::quantized_var_builder::VarBuilder;
use candle::{DType, Device, IndexOp, Module, Result, Tensor, D};
use candle_nn::Activation;
pub use crate::models::mixformer::Config;
const MAX_SEQ_LEN: usize = 4096;
#[derive(Debug, Clone)]
struct Embedding {
... | candle/candle-transformers/src/models/quantized_mixformer.rs/0 | {
"file_path": "candle/candle-transformers/src/models/quantized_mixformer.rs",
"repo_id": "candle",
"token_count": 5892
} | 38 |
use candle::{DType, IndexOp, Result, Tensor};
use candle_nn::{Module, VarBuilder};
use super::image_encoder::ImageEncoderViT;
use super::mask_decoder::MaskDecoder;
use super::prompt_encoder::PromptEncoder;
use super::tiny_vit::{tiny_vit_5m, TinyViT};
const PROMPT_EMBED_DIM: usize = 256;
pub const IMAGE_SIZE: usize = ... | candle/candle-transformers/src/models/segment_anything/sam.rs/0 | {
"file_path": "candle/candle-transformers/src/models/segment_anything/sam.rs",
"repo_id": "candle",
"token_count": 8444
} | 39 |
use crate::models::with_tracing::{linear, linear_no_bias, Linear};
use candle::{DType, Device, Module, Result, Tensor, D};
use candle_nn::{Activation, LayerNorm, VarBuilder};
use serde::Deserialize;
use std::sync::Arc;
// https://huggingface.co/stabilityai/stablelm-3b-4e1t/blob/main/configuration_stablelm.py
#[derive(... | candle/candle-transformers/src/models/stable_lm.rs/0 | {
"file_path": "candle/candle-transformers/src/models/stable_lm.rs",
"repo_id": "candle",
"token_count": 7764
} | 40 |
use super::common::LayerNormNoWeights;
use candle::{Module, Result, Tensor};
use candle_nn::VarBuilder;
#[derive(Debug)]
pub struct MixingResidualBlock {
norm1: LayerNormNoWeights,
depthwise_conv: candle_nn::Conv2d,
norm2: LayerNormNoWeights,
channelwise_lin1: candle_nn::Linear,
channelwise_lin2: c... | candle/candle-transformers/src/models/wuerstchen/paella_vq.rs/0 | {
"file_path": "candle/candle-transformers/src/models/wuerstchen/paella_vq.rs",
"repo_id": "candle",
"token_count": 4078
} | 41 |
use candle_transformers::models::bert;
use wasm_bindgen::prelude::*;
pub use bert::{BertModel, Config, DTYPE};
pub use tokenizers::{PaddingParams, Tokenizer};
#[wasm_bindgen]
extern "C" {
// Use `js_namespace` here to bind `console.log(..)` instead of just
// `log(..)`
#[wasm_bindgen(js_namespace = consol... | candle/candle-wasm-examples/bert/src/lib.rs/0 | {
"file_path": "candle/candle-wasm-examples/bert/src/lib.rs",
"repo_id": "candle",
"token_count": 226
} | 42 |
use crate::console_log;
use crate::worker::{ModelData, Worker, WorkerInput, WorkerOutput};
use std::str::FromStr;
use wasm_bindgen::prelude::*;
use wasm_bindgen_futures::JsFuture;
use yew::{html, Component, Context, Html};
use yew_agent::{Bridge, Bridged};
async fn fetch_url(url: &str) -> Result<Vec<u8>, JsValue> {
... | candle/candle-wasm-examples/llama2-c/src/app.rs/0 | {
"file_path": "candle/candle-wasm-examples/llama2-c/src/app.rs",
"repo_id": "candle",
"token_count": 5458
} | 43 |
## Running Whisper Examples
Here, we provide two examples of how to run Whisper using a Candle-compiled WASM binary and runtimes.
### Pure Rust UI
To build and test the UI made in Rust you will need [Trunk](https://trunkrs.dev/#install)
From the `candle-wasm-examples/whisper` directory run:
Download assets:
```bas... | candle/candle-wasm-examples/whisper/README.md/0 | {
"file_path": "candle/candle-wasm-examples/whisper/README.md",
"repo_id": "candle",
"token_count": 1023
} | 44 |
{
"moz:firefoxOptions": {
"prefs": {
"media.navigator.streams.fake": true,
"media.navigator.permission.disabled": true
},
"args": []
},
"goog:chromeOptions": {
"args": [
"--use-fake-device-for-media-stream",
"--use-fake-ui-for-media-stream"
]
}
}
| candle/candle-wasm-tests/webdriver.json/0 | {
"file_path": "candle/candle-wasm-tests/webdriver.json",
"repo_id": "candle",
"token_count": 143
} | 45 |
---
title: chat-ui
emoji: 🔥
colorFrom: purple
colorTo: purple
sdk: docker
pinned: false
license: apache-2.0
base_path: /chat
app_port: 3000
failure_strategy: rollback
---
# Chat UI
A c... | chat-ui/README.md/0 | {
"file_path": "chat-ui/README.md",
"repo_id": "chat-ui",
"token_count": 9257
} | 46 |
<script lang="ts">
import type { readAndCompressImage } from "browser-image-resizer";
import type { Model } from "$lib/types/Model";
import type { Assistant } from "$lib/types/Assistant";
import { onMount } from "svelte";
import { applyAction, enhance } from "$app/forms";
import { page } from "$app/stores";
imp... | chat-ui/src/lib/components/AssistantSettings.svelte/0 | {
"file_path": "chat-ui/src/lib/components/AssistantSettings.svelte",
"repo_id": "chat-ui",
"token_count": 5719
} | 47 |
<script lang="ts">
import CarbonRotate360 from "~icons/carbon/rotate-360";
export let classNames = "";
</script>
<button
type="button"
on:click
class="btn flex h-8 rounded-lg border bg-white px-3 py-1 text-gray-500 shadow-sm transition-all hover:bg-gray-100 dark:border-gray-600 dark:bg-gray-700 dark:text-gray-30... | chat-ui/src/lib/components/RetryBtn.svelte/0 | {
"file_path": "chat-ui/src/lib/components/RetryBtn.svelte",
"repo_id": "chat-ui",
"token_count": 157
} | 48 |
<script lang="ts">
export let classNames = "";
</script>
<svg
class={classNames}
xmlns="http://www.w3.org/2000/svg"
aria-hidden="true"
fill="currentColor"
focusable="false"
role="img"
width="1em"
height="1em"
preserveAspectRatio="xMidYMid meet"
viewBox="0 0 32 32"
>
<path
d="M28,10V28H10V10H28m0-2H10a2,2... | chat-ui/src/lib/components/icons/IconCopy.svelte/0 | {
"file_path": "chat-ui/src/lib/components/icons/IconCopy.svelte",
"repo_id": "chat-ui",
"token_count": 299
} | 49 |
import { z } from "zod";
import {
embeddingEndpointTei,
embeddingEndpointTeiParametersSchema,
} from "./tei/embeddingEndpoints";
import {
embeddingEndpointTransformersJS,
embeddingEndpointTransformersJSParametersSchema,
} from "./transformersjs/embeddingEndpoints";
import {
embeddingEndpointOpenAI,
embeddingEndpo... | chat-ui/src/lib/server/embeddingEndpoints/embeddingEndpoints.ts/0 | {
"file_path": "chat-ui/src/lib/server/embeddingEndpoints/embeddingEndpoints.ts",
"repo_id": "chat-ui",
"token_count": 478
} | 50 |
import { smallModel } from "$lib/server/models";
import type { Conversation } from "$lib/types/Conversation";
export async function generateFromDefaultEndpoint({
messages,
preprompt,
}: {
messages: Omit<Conversation["messages"][0], "id">[];
preprompt?: string;
}): Promise<string> {
const endpoint = await smallMod... | chat-ui/src/lib/server/generateFromDefaultEndpoint.ts/0 | {
"file_path": "chat-ui/src/lib/server/generateFromDefaultEndpoint.ts",
"repo_id": "chat-ui",
"token_count": 289
} | 51 |
import { writable } from "svelte/store";
export const ERROR_MESSAGES = {
default: "Oops, something went wrong.",
authOnly: "You have to be logged in.",
rateLimited: "You are sending too many messages. Try again later.",
};
export const error = writable<string | null>(null);
| chat-ui/src/lib/stores/errors.ts/0 | {
"file_path": "chat-ui/src/lib/stores/errors.ts",
"repo_id": "chat-ui",
"token_count": 85
} | 52 |
import type { BackendModel } from "$lib/server/models";
export type Model = Pick<
BackendModel,
| "id"
| "name"
| "displayName"
| "websiteUrl"
| "datasetName"
| "promptExamples"
| "parameters"
| "description"
| "logoUrl"
| "modelUrl"
| "datasetUrl"
| "preprompt"
| "multimodal"
| "unlisted"
>;
| chat-ui/src/lib/types/Model.ts/0 | {
"file_path": "chat-ui/src/lib/types/Model.ts",
"repo_id": "chat-ui",
"token_count": 138
} | 53 |
export function deepestChild(el: HTMLElement): HTMLElement {
if (el.lastElementChild && el.lastElementChild.nodeType !== Node.TEXT_NODE) {
return deepestChild(el.lastElementChild as HTMLElement);
}
return el;
}
| chat-ui/src/lib/utils/deepestChild.ts/0 | {
"file_path": "chat-ui/src/lib/utils/deepestChild.ts",
"repo_id": "chat-ui",
"token_count": 74
} | 54 |
export function sum(nums: number[]): number {
return nums.reduce((a, b) => a + b, 0);
}
| chat-ui/src/lib/utils/sum.ts/0 | {
"file_path": "chat-ui/src/lib/utils/sum.ts",
"repo_id": "chat-ui",
"token_count": 35
} | 55 |
<script lang="ts">
import "../styles/main.css";
import { onDestroy } from "svelte";
import { goto, invalidate } from "$app/navigation";
import { base } from "$app/paths";
import { page } from "$app/stores";
import { browser } from "$app/environment";
import {
PUBLIC_APP_DESCRIPTION,
PUBLIC_ORIGIN,
PUBLIC... | chat-ui/src/routes/+layout.svelte/0 | {
"file_path": "chat-ui/src/routes/+layout.svelte",
"repo_id": "chat-ui",
"token_count": 2668
} | 56 |
<script lang="ts">
import ChatWindow from "$lib/components/chat/ChatWindow.svelte";
import { pendingMessage } from "$lib/stores/pendingMessage";
import { isAborted } from "$lib/stores/isAborted";
import { onMount } from "svelte";
import { page } from "$app/stores";
import { goto, invalidateAll } from "$app/naviga... | chat-ui/src/routes/conversation/[id]/+page.svelte/0 | {
"file_path": "chat-ui/src/routes/conversation/[id]/+page.svelte",
"repo_id": "chat-ui",
"token_count": 5239
} | 57 |
import ModelThumbnail from "./ModelThumbnail.svelte";
import { redirect, type RequestHandler } from "@sveltejs/kit";
import type { SvelteComponent } from "svelte";
import { Resvg } from "@resvg/resvg-js";
import satori from "satori";
import { html } from "satori-html";
import InterRegular from "../../../../../static/... | chat-ui/src/routes/models/[...model]/thumbnail.png/+server.ts/0 | {
"file_path": "chat-ui/src/routes/models/[...model]/thumbnail.png/+server.ts",
"repo_id": "chat-ui",
"token_count": 526
} | 58 |
import { base } from "$app/paths";
import { authCondition, requiresUser } from "$lib/server/auth";
import { collections } from "$lib/server/database";
import { fail, type Actions, redirect } from "@sveltejs/kit";
import { ObjectId } from "mongodb";
import { z } from "zod";
import { sha256 } from "$lib/utils/sha256";
i... | chat-ui/src/routes/settings/(nav)/assistants/new/+page.server.ts/0 | {
"file_path": "chat-ui/src/routes/settings/(nav)/assistants/new/+page.server.ts",
"repo_id": "chat-ui",
"token_count": 1538
} | 59 |
<svg xmlns="http://www.w3.org/2000/svg" width="32" height="32" fill="none">
<path
fill="#FFD21E"
d="M4 15.55C4 9.72 8.72 5 14.55 5h4.11a9.34 9.34 0 1 1 0 18.68H7.58l-2.89 2.8a.41.41 0 0 1-.69-.3V15.55Z"
/>
<path
fill="#32343D"
d="M19.63 12.48c.37.14.52.9.9.7.71-.38.98-1.27.6-1.98a1.46 1.46 0 0 0-1.98-.61 1.4... | chat-ui/static/huggingchat/logo.svg/0 | {
"file_path": "chat-ui/static/huggingchat/logo.svg",
"repo_id": "chat-ui",
"token_count": 523
} | 60 |
# This first_section was backported from nginx
loading_datasets: loading
share_dataset: share
quicktour: quickstart
dataset_streaming: stream
torch_tensorflow: use_dataset
splits: loading#slice-splits
processing: process
faiss_and_ea: faiss_es
features: about_dataset_features
using_metrics: how_to_metrics
exploring: ac... | datasets/docs/source/_redirects.yml/0 | {
"file_path": "datasets/docs/source/_redirects.yml",
"repo_id": "datasets",
"token_count": 134
} | 61 |
# Create a dataset card
Each dataset should have a dataset card to promote responsible usage and inform users of any potential biases within the dataset.
This idea was inspired by the Model Cards proposed by [Mitchell, 2018](https://arxiv.org/abs/1810.03993).
Dataset cards help users understand a dataset's contents, t... | datasets/docs/source/dataset_card.mdx/0 | {
"file_path": "datasets/docs/source/dataset_card.mdx",
"repo_id": "datasets",
"token_count": 757
} | 62 |
# Load
Your data can be stored in various places; they can be on your local machine's disk, in a Github repository, and in in-memory data structures like Python dictionaries and Pandas DataFrames. Wherever a dataset is stored, 🤗 Datasets can help you load it.
This guide will show you how to load a dataset from:
- T... | datasets/docs/source/loading.mdx/0 | {
"file_path": "datasets/docs/source/loading.mdx",
"repo_id": "datasets",
"token_count": 7158
} | 63 |
# Stream
Dataset streaming lets you work with a dataset without downloading it.
The data is streamed as you iterate over the dataset.
This is especially helpful when:
- You don't want to wait for an extremely large dataset to download.
- The dataset size exceeds the amount of available disk space on your computer.
- ... | datasets/docs/source/stream.mdx/0 | {
"file_path": "datasets/docs/source/stream.mdx",
"repo_id": "datasets",
"token_count": 5324
} | 64 |
# Copyright 2020 The HuggingFace Datasets Authors.
#
# 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 ... | datasets/metrics/bleu/bleu.py/0 | {
"file_path": "datasets/metrics/bleu/bleu.py",
"repo_id": "datasets",
"token_count": 2139
} | 65 |
# Metric Card for CUAD
## Metric description
This metric wraps the official scoring script for version 1 of the [Contract Understanding Atticus Dataset (CUAD)](https://huggingface.co/datasets/cuad), which is a corpus of more than 13,000 labels in 510 commercial legal contracts that have been manually labeled to ident... | datasets/metrics/cuad/README.md/0 | {
"file_path": "datasets/metrics/cuad/README.md",
"repo_id": "datasets",
"token_count": 2380
} | 66 |
# Copyright 2022 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/mae/mae.py/0 | {
"file_path": "datasets/metrics/mae/mae.py",
"repo_id": "datasets",
"token_count": 1662
} | 67 |
# Copyright 2022 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/perplexity/perplexity.py/0 | {
"file_path": "datasets/metrics/perplexity/perplexity.py",
"repo_id": "datasets",
"token_count": 3550
} | 68 |
# 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/spearmanr/spearmanr.py/0 | {
"file_path": "datasets/metrics/spearmanr/spearmanr.py",
"repo_id": "datasets",
"token_count": 1942
} | 69 |
# Metric Card for XNLI
## Metric description
The XNLI metric allows to evaluate a model's score on the [XNLI dataset](https://huggingface.co/datasets/xnli), which is a subset of a few thousand examples from the [MNLI dataset](https://huggingface.co/datasets/glue/viewer/mnli) that have been translated into a 14 differ... | datasets/metrics/xnli/README.md/0 | {
"file_path": "datasets/metrics/xnli/README.md",
"repo_id": "datasets",
"token_count": 1226
} | 70 |
#!/usr/bin/env python
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test import TestComm... | datasets/src/datasets/commands/datasets_cli.py/0 | {
"file_path": "datasets/src/datasets/commands/datasets_cli.py",
"repo_id": "datasets",
"token_count": 473
} | 71 |
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.download_config import DownloadConfig
from ..download.streaming_download_manager import xopen, ... | datasets/src/datasets/features/audio.py/0 | {
"file_path": "datasets/src/datasets/features/audio.py",
"repo_id": "datasets",
"token_count": 5335
} | 72 |
# Copyright 2020 The HuggingFace Datasets Authors.
#
# 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 ... | datasets/src/datasets/inspect.py/0 | {
"file_path": "datasets/src/datasets/inspect.py",
"repo_id": "datasets",
"token_count": 9937
} | 73 |
# Copyright 2020 The HuggingFace Datasets Authors and the TensorFlow Datasets Authors.
#
# 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
#
# U... | datasets/src/datasets/splits.py/0 | {
"file_path": "datasets/src/datasets/splits.py",
"repo_id": "datasets",
"token_count": 9598
} | 74 |
import os
from apache_beam.io.filesystems import FileSystems
from apache_beam.pipeline import Pipeline
from .logging import get_logger
CHUNK_SIZE = 2 << 20 # 2mb
logger = get_logger(__name__)
class BeamPipeline(Pipeline):
"""Wrapper over `apache_beam.pipeline.Pipeline` for convenience"""
def is_local(se... | datasets/src/datasets/utils/beam_utils.py/0 | {
"file_path": "datasets/src/datasets/utils/beam_utils.py",
"repo_id": "datasets",
"token_count": 847
} | 75 |
{
"language": [
"found",
"crowdsourced",
"expert-generated",
"machine-generated",
"other"
],
"annotations": [
"found",
"crowdsourced",
"expert-generated",
"machine-generated",
"no-annotation",
"other"
]
}
| datasets/src/datasets/utils/resources/creators.json/0 | {
"file_path": "datasets/src/datasets/utils/resources/creators.json",
"repo_id": "datasets",
"token_count": 119
} | 76 |
## Add Dummy data test
**Important** In order to pass the `load_dataset_<dataset_name>` test, dummy data is required for all possible config names.
First we distinguish between datasets scripts that
- A) have no config class and
- B) have a config class
For A) the dummy data folder structure, will always look as fol... | datasets/tests/README.md/0 | {
"file_path": "datasets/tests/README.md",
"repo_id": "datasets",
"token_count": 928
} | 77 |
import os
import random
import tempfile
import unittest
import numpy as np
import pandas as pd
import pyarrow as pa
import pytest
from absl.testing import parameterized
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features import Array2D, Array3D, Array4D, Array5D, Value
from datasets.f... | datasets/tests/features/test_array_xd.py/0 | {
"file_path": "datasets/tests/features/test_array_xd.py",
"repo_id": "datasets",
"token_count": 9826
} | 78 |
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def _check_text_dataset(dataset, expected_features):
assert isinstance(dataset, Dataset)
... | datasets/tests/io/test_text.py/0 | {
"file_path": "datasets/tests/io/test_text.py",
"repo_id": "datasets",
"token_count": 1833
} | 79 |
import copy
import os
from pathlib import Path
from typing import List
from unittest.mock import patch
import fsspec
import pytest
from fsspec.registry import _registry as _fsspec_registry
from fsspec.spec import AbstractFileSystem
from datasets.data_files import (
DataFilesDict,
DataFilesList,
DataFilesP... | datasets/tests/test_data_files.py/0 | {
"file_path": "datasets/tests/test_data_files.py",
"repo_id": "datasets",
"token_count": 12329
} | 80 |
import os
from pathlib import Path
import pytest
from datasets.inspect import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_default_config_name,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
from datasets.packaged_modules.csv import csv
... | datasets/tests/test_inspect.py/0 | {
"file_path": "datasets/tests/test_inspect.py",
"repo_id": "datasets",
"token_count": 2081
} | 81 |
from copy import deepcopy
from unittest.case import TestCase
import pytest
from datasets.arrow_dataset import Dataset
from datasets.features import Audio, ClassLabel, Features, Image, Sequence, Value
from datasets.info import DatasetInfo
from datasets.tasks import (
AudioClassification,
AutomaticSpeechRecogni... | datasets/tests/test_tasks.py/0 | {
"file_path": "datasets/tests/test_tasks.py",
"repo_id": "datasets",
"token_count": 4249
} | 82 |
# The “Deep” in Reinforcement Learning [[deep-rl]]
<Tip>
What we've talked about so far is Reinforcement Learning. But where does the "Deep" come into play?
</Tip>
Deep Reinforcement Learning introduces **deep neural networks to solve Reinforcement Learning problems** — hence the name “deep”.
For instance, in the ne... | deep-rl-class/units/en/unit1/deep-rl.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit1/deep-rl.mdx",
"repo_id": "deep-rl-class",
"token_count": 310
} | 83 |
# Introduction to Q-Learning [[introduction-q-learning]]
<img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit3/thumbnail.jpg" alt="Unit 2 thumbnail" width="100%">
In the first unit of this class, we learned about Reinforcement Learning (RL), the RL process, and the ... | deep-rl-class/units/en/unit2/introduction.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit2/introduction.mdx",
"repo_id": "deep-rl-class",
"token_count": 466
} | 84 |
# Hands-on [[hands-on]]
<CourseFloatingBanner classNames="absolute z-10 right-0 top-0"
notebooks={[
{label: "Google Colab", value: "https://colab.research.google.com/github/huggingface/deep-rl-class/blob/main/notebooks/unit3/unit3.ipynb"}
]}
askForHelpUrl="http://hf.co/join/discor... | deep-rl-class/units/en/unit3/hands-on.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit3/hands-on.mdx",
"repo_id": "deep-rl-class",
"token_count": 5087
} | 85 |
# Hands-on
<CourseFloatingBanner classNames="absolute z-10 right-0 top-0"
notebooks={[
{label: "Google Colab", value: "https://colab.research.google.com/github/huggingface/deep-rl-class/blob/main/notebooks/unit5/unit5.ipynb"}
]}
askForHelpUrl="http://hf.co/join/discord" />
We learned what ML-Agents is and how ... | deep-rl-class/units/en/unit5/hands-on.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit5/hands-on.mdx",
"repo_id": "deep-rl-class",
"token_count": 5146
} | 86 |
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