Instructions to use underscore2/llama3-8b-bluesky-engagement-kto with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use underscore2/llama3-8b-bluesky-engagement-kto with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("underscore2/llama3-8b-bluesky-engagement-kto", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
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Download README.md from underscore2/llama3-8b-bluesky-engagement-kto: direct link, hf CLI and curl.
- Browser
- Download file 600 Bytes
-
https://huggingface.co/underscore2/llama3-8b-bluesky-engagement-kto/resolve/91a647806c3c2b68b0da6c8b13d463c63f7f467b/README.md
- Command line
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hf download hf://underscore2/llama3-8b-bluesky-engagement-kto@91a647806c3c2b68b0da6c8b13d463c63f7f467b/README.md
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curl -L -o README.md https://huggingface.co/underscore2/llama3-8b-bluesky-engagement-kto/resolve/91a647806c3c2b68b0da6c8b13d463c63f7f467b/README.md
600 Bytes
metadata
base_model: unsloth/llama-3-8b-instruct-bnb-4bit
tags:
- text-generation-inference
- transformers
- unsloth
- llama
license: apache-2.0
language:
- en
Uploaded finetuned model
- Developed by: underscore2
- License: apache-2.0
- Finetuned from model : unsloth/llama-3-8b-instruct-bnb-4bit
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
