repo_id stringlengths 15 89 | file_path stringlengths 27 180 | content stringlengths 1 2.23M | __index_level_0__ int64 0 0 |
|---|---|---|---|
hf_public_repos/diffusers/src/diffusers/models | hf_public_repos/diffusers/src/diffusers/models/autoencoders/autoencoder_tiny.py | # Copyright 2023 Ollin Boer Bohan and 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 ... | 0 |
hf_public_repos/diffusers/src/diffusers/models | hf_public_repos/diffusers/src/diffusers/models/autoencoders/__init__.py | from .autoencoder_asym_kl import AsymmetricAutoencoderKL
from .autoencoder_kl import AutoencoderKL
from .autoencoder_kl_temporal_decoder import AutoencoderKLTemporalDecoder
from .autoencoder_tiny import AutoencoderTiny
from .consistency_decoder_vae import ConsistencyDecoderVAE
| 0 |
hf_public_repos/diffusers/src/diffusers/models | hf_public_repos/diffusers/src/diffusers/models/autoencoders/autoencoder_asym_kl.py | # 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... | 0 |
hf_public_repos/diffusers/src/diffusers/models | hf_public_repos/diffusers/src/diffusers/models/autoencoders/vae.py | # 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... | 0 |
hf_public_repos/diffusers/src/diffusers/models | hf_public_repos/diffusers/src/diffusers/models/autoencoders/consistency_decoder_vae.py | # 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... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/utils/dummy_torch_and_torchsde_objects.py | # This file is autogenerated by the command `make fix-copies`, do not edit.
from ..utils import DummyObject, requires_backends
class DPMSolverSDEScheduler(metaclass=DummyObject):
_backends = ["torch", "torchsde"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch", "torchsde"])
... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/utils/accelerate_utils.py | # 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... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/utils/pil_utils.py | from typing import List
import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image
if version.parse(version.parse(PIL.__version__).base_version) >= version.parse("9.1.0"):
PIL_INTERPOLATION = {
"linear": PIL.Image.Resampling.BILINEAR,
"bilinear": PIL.Image.Resampling... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/utils/doc_utils.py | # 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... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/utils/dummy_torch_and_scipy_objects.py | # This file is autogenerated by the command `make fix-copies`, do not edit.
from ..utils import DummyObject, requires_backends
class LMSDiscreteScheduler(metaclass=DummyObject):
_backends = ["torch", "scipy"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch", "scipy"])
@class... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/utils/dummy_torch_and_transformers_and_k_diffusion_objects.py | # This file is autogenerated by the command `make fix-copies`, do not edit.
from ..utils import DummyObject, requires_backends
class StableDiffusionKDiffusionPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers", "k_diffusion"]
def __init__(self, *args, **kwargs):
requires_backends(se... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/utils/outputs.py | # 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... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/utils/import_utils.py | # 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... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/utils/model_card_template.md | ---
{{ card_data }}
---
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->
# {{ model_name | default("Diffusion Model") }}
## Model description
This diffusion model is trai... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/utils/deprecation_utils.py | import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def deprecate(*args, take_from: Optional[Union[Dict, Any]] = None, standard_warn=True, stacklevel=2):
from .. import __version__
deprecated_kwargs = take_from
values = ()
if not isinstance(args... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py | # This file is autogenerated by the command `make fix-copies`, do not edit.
from ..utils import DummyObject, requires_backends
class AltDiffusionImg2ImgPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch", "transf... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/utils/dynamic_modules_utils.py | # 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... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/utils/versions.py | # Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/utils/dummy_note_seq_objects.py | # This file is autogenerated by the command `make fix-copies`, do not edit.
from ..utils import DummyObject, requires_backends
class MidiProcessor(metaclass=DummyObject):
_backends = ["note_seq"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["note_seq"])
@classmethod
def from... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/utils/dummy_torch_and_transformers_and_onnx_objects.py | # This file is autogenerated by the command `make fix-copies`, do not edit.
from ..utils import DummyObject, requires_backends
class OnnxStableDiffusionImg2ImgPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers", "onnx"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/utils/testing_utils.py | import functools
import importlib
import inspect
import io
import logging
import multiprocessing
import os
import random
import re
import struct
import sys
import tempfile
import time
import unittest
import urllib.parse
from contextlib import contextmanager
from distutils.util import strtobool
from io import BytesIO, S... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/utils/hub_utils.py | # 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... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/utils/dummy_torch_and_librosa_objects.py | # This file is autogenerated by the command `make fix-copies`, do not edit.
from ..utils import DummyObject, requires_backends
class AudioDiffusionPipeline(metaclass=DummyObject):
_backends = ["torch", "librosa"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch", "librosa"])
... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/utils/__init__.py | # Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/utils/loading_utils.py | import os
from typing import Callable, Union
import PIL.Image
import PIL.ImageOps
import requests
def load_image(
image: Union[str, PIL.Image.Image], convert_method: Callable[[PIL.Image.Image], PIL.Image.Image] = None
) -> PIL.Image.Image:
"""
Loads `image` to a PIL Image.
Args:
image (`str`... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/utils/logging.py | # coding=utf-8
# Copyright 2023 Optuna, Hugging Face
#
# 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 o... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/utils/state_dict_utils.py | # 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... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/utils/dummy_transformers_and_torch_and_note_seq_objects.py | # This file is autogenerated by the command `make fix-copies`, do not edit.
from ..utils import DummyObject, requires_backends
class SpectrogramDiffusionPipeline(metaclass=DummyObject):
_backends = ["transformers", "torch", "note_seq"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tr... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/utils/torch_utils.py | # 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... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/utils/dummy_flax_objects.py | # This file is autogenerated by the command `make fix-copies`, do not edit.
from ..utils import DummyObject, requires_backends
class FlaxControlNetModel(metaclass=DummyObject):
_backends = ["flax"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["flax"])
@classmethod
def from_c... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/utils/dummy_flax_and_transformers_objects.py | # This file is autogenerated by the command `make fix-copies`, do not edit.
from ..utils import DummyObject, requires_backends
class FlaxStableDiffusionControlNetPipeline(metaclass=DummyObject):
_backends = ["flax", "transformers"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["flax",... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/utils/export_utils.py | import io
import random
import struct
import tempfile
from contextlib import contextmanager
from typing import List, Union
import numpy as np
import PIL.Image
import PIL.ImageOps
from .import_utils import (
BACKENDS_MAPPING,
is_opencv_available,
)
from .logging import get_logger
global_rng = random.Random()... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/utils/dummy_onnx_objects.py | # This file is autogenerated by the command `make fix-copies`, do not edit.
from ..utils import DummyObject, requires_backends
class OnnxRuntimeModel(metaclass=DummyObject):
_backends = ["onnx"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["onnx"])
@classmethod
def from_conf... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/utils/constants.py | # Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/utils/peft_utils.py | # 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... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/utils/dummy_pt_objects.py | # This file is autogenerated by the command `make fix-copies`, do not edit.
from ..utils import DummyObject, requires_backends
class AsymmetricAutoencoderKL(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
@classmethod
def ... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/commands/__init__.py | # 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... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/commands/env.py | # 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... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/commands/fp16_safetensors.py | # 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... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/commands/diffusers_cli.py | #!/usr/bin/env python
# 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... | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/experimental/README.md | # 🧨 Diffusers Experimental
We are adding experimental code to support novel applications and usages of the Diffusers library.
Currently, the following experiments are supported:
* Reinforcement learning via an implementation of the [Diffuser](https://arxiv.org/abs/2205.09991) model. | 0 |
hf_public_repos/diffusers/src/diffusers | hf_public_repos/diffusers/src/diffusers/experimental/__init__.py | from .rl import ValueGuidedRLPipeline
| 0 |
hf_public_repos/diffusers/src/diffusers/experimental | hf_public_repos/diffusers/src/diffusers/experimental/rl/value_guided_sampling.py | # 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... | 0 |
hf_public_repos/diffusers/src/diffusers/experimental | hf_public_repos/diffusers/src/diffusers/experimental/rl/__init__.py | from .value_guided_sampling import ValueGuidedRLPipeline
| 0 |
hf_public_repos | hf_public_repos/trl/.pre-commit-config.yaml | repos:
- repo: https://github.com/PyCQA/isort
rev: 5.12.0
hooks:
- id: isort
args:
- --profile=black
- --skip-glob=wandb/**/*
- --thirdparty=wandb
- repo: https://github.com/myint/autoflake
rev: v1.4
hooks:
- id: autoflake
args:
- -... | 0 |
hf_public_repos | hf_public_repos/trl/setup.cfg | [metadata]
license_file = LICENSE
[isort]
ensure_newline_before_comments = True
force_grid_wrap = 0
include_trailing_comma = True
line_length = 119
lines_after_imports = 2
multi_line_output = 3
use_parentheses = True
| 0 |
hf_public_repos | hf_public_repos/trl/README.md | <div style="text-align: center">
<img src="https://huggingface.co/datasets/trl-internal-testing/example-images/resolve/main/images/trl_banner_dark.png">
</div>
# TRL - Transformer Reinforcement Learning
> Full stack transformer language models with reinforcement learning.
<p align="center">
<a href="https://githu... | 0 |
hf_public_repos | hf_public_repos/trl/pyproject.toml | [tool.black]
line-length = 119
target-version = ['py38']
[tool.ruff]
ignore = ["E501", "E741", "W605"]
select = ["E", "F", "I", "W"]
line-length = 119
# Ignore import violations in all `__init__.py` files.
[tool.ruff.per-file-ignores]
"__init__.py" = ["E402", "F401", "F403", "F811"]
[tool.ruff.isort]
lines-after-imp... | 0 |
hf_public_repos | hf_public_repos/trl/CONTRIBUTING.md | # How to contribute
## How to get started
Before you start contributing make sure you installed all the dev tools:
```bash
pip install -e ".[dev]"
```
## Did you find a bug?
* Ensure the bug was not already reported by searching on GitHub under Issues.
* If you're unable to find an open issue addressing the proble... | 0 |
hf_public_repos | hf_public_repos/trl/requirements.txt | datasets>=1.17.0
torch>=1.4.0
tqdm
transformers
accelerate
peft>=0.3.0
tyro>=0.5.7 | 0 |
hf_public_repos | hf_public_repos/trl/setup.py | """ trl is an open library for RL with transformer models.
Note:
VERSION needs to be formatted following the MAJOR.MINOR.PATCH convention
(we need to follow this convention to be able to retrieve versioned scripts)
Simple check list for release from AllenNLP repo: https://github.com/allenai/allennlp/blob/maste... | 0 |
hf_public_repos | hf_public_repos/trl/CITATION.cff | cff-version: 1.2.0
title: 'TRL: Transformer Reinforcement Learning'
message: >-
If you use this software, please cite it using the
metadata from this file.
type: software
authors:
- given-names: Leandro
family-names: von Werra
- given-names: Younes
family-names: Belkada
- given-names: Lewis
family... | 0 |
hf_public_repos | hf_public_repos/trl/MANIFEST.in | include settings.ini
include LICENSE
include CONTRIBUTING.md
include README.md
recursive-exclude * __pycache__
| 0 |
hf_public_repos | hf_public_repos/trl/Makefile | .PHONY: test precommit benchmark_core benchmark_aux common_tests slow_tests test_examples tests_gpu
check_dirs := examples tests trl
ACCELERATE_CONFIG_PATH = `pwd`/examples/accelerate_configs
COMMAND_FILES_PATH = `pwd`/commands
test:
python -m pytest -n auto --dist=loadfile -s -v ./tests/
precommit:
pre-commit ru... | 0 |
hf_public_repos | hf_public_repos/trl/LICENSE | Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
1. Definitions.
"License" shall mean the terms and conditions for use, reproduction,
... | 0 |
hf_public_repos/trl | hf_public_repos/trl/scripts/log_example_reports.py | # 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 required by applicabl... | 0 |
hf_public_repos/trl | hf_public_repos/trl/scripts/stale.py | # Copyright 2023 The HuggingFace Team, the AllenNLP library authors. 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
#
... | 0 |
hf_public_repos/trl | hf_public_repos/trl/scripts/log_reports.py | # 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 required by applicabl... | 0 |
hf_public_repos/trl | hf_public_repos/trl/examples/hello_world.py | # 0. imports
import torch
from transformers import GPT2Tokenizer
from trl import AutoModelForCausalLMWithValueHead, PPOConfig, PPOTrainer
# 1. load a pretrained model
model = AutoModelForCausalLMWithValueHead.from_pretrained("gpt2")
model_ref = AutoModelForCausalLMWithValueHead.from_pretrained("gpt2")
tokenizer = GP... | 0 |
hf_public_repos/trl | hf_public_repos/trl/examples/README.md | # Examples
Please check out https://huggingface.co/docs/trl/example_overview for documentation on our examples. | 0 |
hf_public_repos/trl/examples | hf_public_repos/trl/examples/scripts/ppo.py | # coding=utf-8
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... | 0 |
hf_public_repos/trl/examples | hf_public_repos/trl/examples/scripts/sft.py | # coding=utf-8
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... | 0 |
hf_public_repos/trl/examples | hf_public_repos/trl/examples/scripts/ddpo.py | # Copyright 2023 metric-space, 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 require... | 0 |
hf_public_repos/trl/examples | hf_public_repos/trl/examples/scripts/dpo.py | # coding=utf-8
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... | 0 |
hf_public_repos/trl/examples | hf_public_repos/trl/examples/scripts/ppo_multi_adapter.py | # coding=utf-8
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... | 0 |
hf_public_repos/trl/examples | hf_public_repos/trl/examples/scripts/reward_modeling.py | # coding=utf-8
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... | 0 |
hf_public_repos/trl/examples | hf_public_repos/trl/examples/research_projects/README.md | # Research projects that use TRL
Welcome to the research projects folder! Here you can find the scripts used for some research projects that used TRL and maintained by the developers and the community (LM de-toxification, Stack-Llama, etc.). Check out the READMEs in the subfolders for more information!
- [De-detoxify... | 0 |
hf_public_repos/trl/examples/research_projects/stack_llama_2 | hf_public_repos/trl/examples/research_projects/stack_llama_2/scripts/README.md | # DPO pipeline for the creation of StackLlaMa 2: a Stack exchange llama-v2-7b model
## Prerequisites
Install all the dependencies in the `requirements.txt`:
```
$ pip install -U -r requirements.txt
```
Since we will use `accelerate` for training, make sure to run:
```
$ accelerate config
```
## Training
There wer... | 0 |
hf_public_repos/trl/examples/research_projects/stack_llama_2 | hf_public_repos/trl/examples/research_projects/stack_llama_2/scripts/sft_llama2.py | # Fine-Tune Llama2-7b on SE paired dataset
import os
from dataclasses import dataclass, field
from typing import Optional
import torch
from accelerate import Accelerator
from datasets import load_dataset
from peft import AutoPeftModelForCausalLM, LoraConfig
from tqdm import tqdm
from transformers import AutoModelForCa... | 0 |
hf_public_repos/trl/examples/research_projects/stack_llama_2 | hf_public_repos/trl/examples/research_projects/stack_llama_2/scripts/requirements.txt | transformers
trl
peft
accelerate
datasets
bitsandbytes
wandb
| 0 |
hf_public_repos/trl/examples/research_projects/stack_llama_2 | hf_public_repos/trl/examples/research_projects/stack_llama_2/scripts/dpo_llama2.py | # 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 ... | 0 |
hf_public_repos/trl/examples/research_projects | hf_public_repos/trl/examples/research_projects/tools/triviaqa.py | # coding=utf-8
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... | 0 |
hf_public_repos/trl/examples/research_projects | hf_public_repos/trl/examples/research_projects/tools/python_interpreter.py | # coding=utf-8
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... | 0 |
hf_public_repos/trl/examples/research_projects | hf_public_repos/trl/examples/research_projects/tools/calculator.py | # coding=utf-8
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... | 0 |
hf_public_repos/trl/examples/research_projects | hf_public_repos/trl/examples/research_projects/toxicity/README.md | # 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
```
| 0 |
hf_public_repos/trl/examples/research_projects/toxicity | hf_public_repos/trl/examples/research_projects/toxicity/scripts/evaluate-toxicity.py | import argparse
import csv
import evaluate
import numpy as np
import torch
from datasets import load_dataset
from tqdm import tqdm
from transformers import AutoModelForCausalLM, AutoTokenizer
from trl.import_utils import is_npu_available, is_xpu_available
toxicity = evaluate.load("ybelkada/toxicity", "DaNLP/da-elec... | 0 |
hf_public_repos/trl/examples/research_projects/toxicity | hf_public_repos/trl/examples/research_projects/toxicity/scripts/gpt-j-6b-toxicity.py | # coding=utf-8
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... | 0 |
hf_public_repos/trl/examples/research_projects/stack_llama | hf_public_repos/trl/examples/research_projects/stack_llama/scripts/supervised_finetuning.py | import argparse
import os
from accelerate import Accelerator
from datasets import load_dataset
from peft import LoraConfig
from tqdm import tqdm
from transformers import AutoModelForCausalLM, AutoTokenizer, TrainingArguments, logging, set_seed
from trl import SFTTrainer
from trl.trainer import ConstantLengthDataset
... | 0 |
hf_public_repos/trl/examples/research_projects/stack_llama | hf_public_repos/trl/examples/research_projects/stack_llama/scripts/rl_training.py | # 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... | 0 |
hf_public_repos/trl/examples/research_projects/stack_llama | hf_public_repos/trl/examples/research_projects/stack_llama/scripts/merge_peft_adapter.py | from dataclasses import dataclass, field
from typing import Optional
import torch
from peft import PeftConfig, PeftModel
from transformers import AutoModelForCausalLM, AutoModelForSequenceClassification, AutoTokenizer, HfArgumentParser
@dataclass
class ScriptArguments:
"""
The input names representing the Ad... | 0 |
hf_public_repos/trl/examples/research_projects/stack_llama | hf_public_repos/trl/examples/research_projects/stack_llama/scripts/README.md | # RLHF pipeline for the creation of StackLLaMa: a Stack exchange llama-7b model.
There were three main steps to the training process:
1. Supervised fine-tuning of the base llama-7b model to create llama-7b-se:
- `torchrun --nnodes 1 --nproc_per_node 8 examples/research_projects/stack_llama/scripts/supervised_finet... | 0 |
hf_public_repos/trl/examples/research_projects/stack_llama | hf_public_repos/trl/examples/research_projects/stack_llama/scripts/reward_modeling.py | from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import evaluate
import numpy as np
import torch
import torch.nn as nn
from datasets import load_dataset
from peft import LoraConfig, TaskType, get_peft_model
from transformers import (
AutoModelForSequenceClassification,
... | 0 |
hf_public_repos/trl/examples | hf_public_repos/trl/examples/notebooks/gpt2-sentiment.ipynb | %load_ext autoreload
%autoreload 2%pip install transformers trl wandbimport torch
from tqdm import tqdm
import pandas as pd
tqdm.pandas()
from transformers import pipeline, AutoTokenizer
from datasets import load_dataset
from trl import PPOTrainer, PPOConfig, AutoModelForCausalLMWithValueHead
from trl.core import Le... | 0 |
hf_public_repos/trl/examples | hf_public_repos/trl/examples/notebooks/README.md | # Notebooks
This directory contains a collection of Jupyter notebooks that demonstrate how to use the TRL library in different applications.
- [`best_of_n.ipynb`](https://github.com/huggingface/trl/tree/main/examples/notebooks/best_of_n.ipynb): This notebook demonstrates how to use the "Best of N" sampling strategy u... | 0 |
hf_public_repos/trl/examples | hf_public_repos/trl/examples/notebooks/best_of_n.ipynb | %pip install transformers trlimport torch
import pandas as pd
from transformers import pipeline, AutoTokenizer
from datasets import load_dataset
from trl import AutoModelForCausalLMWithValueHead
from trl.core import LengthSampler
device = 0 if torch.cuda.is_available() else "cpu"ref_model_name = "lvwerra/gpt2-imdb"
m... | 0 |
hf_public_repos/trl/examples | hf_public_repos/trl/examples/notebooks/gpt2-sentiment-control.ipynb | %load_ext autoreload
%autoreload 2import random
import torch
import wandb
import time
import os
from tqdm import tqdm
import numpy as np
import pandas as pd
from random import choices
import matplotlib.pyplot as plt
tqdm.pandas()
from datasets import load_dataset
from transformers import AutoTokenizer, pipeline
fro... | 0 |
hf_public_repos/trl/examples | hf_public_repos/trl/examples/accelerate_configs/single_gpu.yaml | compute_environment: LOCAL_MACHINE
debug: false
distributed_type: "NO"
downcast_bf16: 'no'
gpu_ids: all
machine_rank: 0
main_training_function: main
mixed_precision: 'bf16'
num_machines: 1
num_processes: 8
rdzv_backend: static
same_network: true
tpu_env: []
tpu_use_cluster: false
tpu_use_sudo: false
use_cpu: false
| 0 |
hf_public_repos/trl/examples | hf_public_repos/trl/examples/accelerate_configs/deepspeed_zero3.yaml | compute_environment: LOCAL_MACHINE
debug: false
deepspeed_config:
deepspeed_multinode_launcher: standard
gradient_accumulation_steps: 1
offload_optimizer_device: none
offload_param_device: none
zero3_init_flag: true
zero3_save_16bit_model: true
zero_stage: 3
distributed_type: DEEPSPEED
downcast_bf16: 'no'... | 0 |
hf_public_repos/trl/examples | hf_public_repos/trl/examples/accelerate_configs/deepspeed_zero2.yaml | compute_environment: LOCAL_MACHINE
debug: false
deepspeed_config:
deepspeed_multinode_launcher: standard
gradient_accumulation_steps: 1
offload_optimizer_device: none
offload_param_device: none
zero3_init_flag: false
zero_stage: 2
distributed_type: DEEPSPEED
downcast_bf16: 'no'
machine_rank: 0
main_training... | 0 |
hf_public_repos/trl/examples | hf_public_repos/trl/examples/accelerate_configs/multi_gpu.yaml | compute_environment: LOCAL_MACHINE
debug: false
distributed_type: MULTI_GPU
downcast_bf16: 'no'
gpu_ids: all
machine_rank: 0
main_training_function: main
mixed_precision: 'bf16'
num_machines: 1
num_processes: 8
rdzv_backend: static
same_network: true
tpu_env: []
tpu_use_cluster: false
tpu_use_sudo: false
use_cpu: false... | 0 |
hf_public_repos/trl/examples | hf_public_repos/trl/examples/accelerate_configs/deepspeed_zero1.yaml | compute_environment: LOCAL_MACHINE
debug: false
deepspeed_config:
deepspeed_multinode_launcher: standard
gradient_accumulation_steps: 1
zero3_init_flag: false
zero_stage: 1
distributed_type: DEEPSPEED
downcast_bf16: 'no'
machine_rank: 0
main_training_function: main
mixed_precision: 'bf16'
num_machines: 1
num_pr... | 0 |
hf_public_repos/trl | hf_public_repos/trl/benchmark/benchmark.py | import argparse
import math
import os
import shlex
import subprocess
import uuid
from distutils.util import strtobool
import requests
def parse_args():
# fmt: off
parser = argparse.ArgumentParser()
parser.add_argument("--command", type=str, default="",
help="the command to run")
parser.add_ar... | 0 |
hf_public_repos/trl | hf_public_repos/trl/benchmark/benchmark_level1_plot.sh | # pip install openrlbenchmark==0.2.1a5
# see https://github.com/openrlbenchmark/openrlbenchmark#get-started for documentation
echo "we deal with $TAGS_STRING"
python -m openrlbenchmark.rlops_multi_metrics \
--filters '?we=huggingface&wpn=trl&xaxis=_step&ceik=trl_ppo_trainer_config.value.reward_model&cen=trl_ppo_tr... | 0 |
hf_public_repos/trl | hf_public_repos/trl/benchmark/post_github_comment.py | 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... | 0 |
hf_public_repos/trl | hf_public_repos/trl/benchmark/benchmark_level3.sh | ## w/ and w/o gradient accumulation
python benchmark/benchmark.py \
--command "python examples/scripts/ppo.py --ppo_config.exp_name ppo_step_grad_accu --ppo_config.mini_batch_size 1 --ppo_config.gradient_accumulation_steps 128 --ppo_config.log_with wandb" \
--num-seeds 3 \
--start-seed 1 \
--workers 10 ... | 0 |
hf_public_repos/trl | hf_public_repos/trl/benchmark/benchmark_and_report.sh | #### Step 1: create a work directory:
# this is necessary because another github action job will remove
# the entire directory, which slurm depends on.
# https://stackoverflow.com/questions/4632028/how-to-create-a-temporary-directory
MY_SLURM_TMP_DIR=/fsx/costa/slurm_tmpdir
mkdir -p $MY_SLURM_TMP_DIR
WORK_DIR=`mktemp -... | 0 |
hf_public_repos/trl | hf_public_repos/trl/benchmark/upload_benchmark.py | 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... | 0 |
hf_public_repos/trl | hf_public_repos/trl/benchmark/benchmark_level1.sh | # hello world experiment
python benchmark/benchmark.py \
--command "python examples/scripts/ppo.py --ppo_config.log_with wandb" \
--num-seeds 3 \
--start-seed 1 \
--workers 10 \
--slurm-nodes 1 \
--slurm-gpus-per-task 1 \
--slurm-ntasks 1 \
--slurm-total-cpus 12 \
--slurm-template-pa... | 0 |
hf_public_repos/trl | hf_public_repos/trl/benchmark/benchmark_level2_plot.sh | # pip install openrlbenchmark==0.2.1a5
# see https://github.com/openrlbenchmark/openrlbenchmark#get-started for documentation
echo "we deal with $TAGS_STRING"
python -m openrlbenchmark.rlops_multi_metrics \
--filters '?we=huggingface&wpn=trl&xaxis=_step&ceik=trl_ppo_trainer_config.value.reward_model&cen=trl_ppo_tr... | 0 |
hf_public_repos/trl | hf_public_repos/trl/benchmark/benchmark_level2.sh | # compound experiments: gpt2xl + grad_accu
python benchmark/benchmark.py \
--command "python examples/scripts/ppo.py --ppo_config.exp_name ppo_gpt2xl_grad_accu --ppo_config.model_name gpt2-xl --ppo_config.mini_batch_size 16 --ppo_config.gradient_accumulation_steps 8 --ppo_config.log_with wandb" \
--num-seeds 3 ... | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.