General
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version: '3'
services:
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Explore
Find agent skills by outcome
125,924 skills indexed with the new KISS metadata standard.
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.venv
.github
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out/
7B/
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QLoRA: Efficient Finetuning of Quantized LLMs
| [Paper](https://arxiv.org/abs/2305.14314) | [Adapter Weights](https://huggingface.co/timdettmers) | [Demo](https://huggingface.co/spaces/uwnlp/guanaco-playground-tgi) |
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wandb/
output/
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project:
type: website
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version: '3.8'
services:
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codecov:
require_ci_to_pass: yes
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default_language_version:
python: python3
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data/*.jsonl filter=lfs diff=lfs merge=lfs -text
generic skill
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<p align="center">
<picture>
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FAQs
- Can you train StableLM with this? Yes, but only with a single GPU atm. Multi GPU support is coming soon! Just waiting on this [PR](https://github.com/huggingface/transformers/pull/22874)
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**/axolotl.egg-info
configs
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[bandit]
exclude = tests
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root = true
[*]
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[run]
source = axolotl
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yaml-language-server: $schema=https://coderabbit.ai/integrations/schema.v2.json
language: "en-US"
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Byte-compiled / optimized / DLL files
__pycache__/
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<p align="center">
<img src="https://raw.githubusercontent.com/huggingface/alignment-handbook/main/assets/handbook.png">
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Making a release
> [!NOTE]
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How to contribute to TRL?
Everyone is welcome to contribute, and we value everybody's contribution. Code contributions are not the only way to help the community. Answering questions, helping others, and improving the documentation are also immensely valuable.
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repos:
- repo: https://github.com/astral-sh/ruff-pre-commit
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*.bak
.gitattributes
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TRL - Transformer Reinforcement Learning
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