Instructions to use baby-dev/682e4ea7-8030-43a9-9e1d-02564a2075cd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use baby-dev/682e4ea7-8030-43a9-9e1d-02564a2075cd with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Llama-3.1-Storm-8B") model = PeftModel.from_pretrained(base_model, "baby-dev/682e4ea7-8030-43a9-9e1d-02564a2075cd") - Notebooks
- Google Colab
- Kaggle
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Download README.md from baby-dev/682e4ea7-8030-43a9-9e1d-02564a2075cd: direct link, hf CLI and curl.
- Browser
- Download file 1.12 kB
-
https://huggingface.co/baby-dev/682e4ea7-8030-43a9-9e1d-02564a2075cd/resolve/main/README.md
- Command line
-
hf download hf://baby-dev/682e4ea7-8030-43a9-9e1d-02564a2075cd/README.md
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curl -L -o README.md https://huggingface.co/baby-dev/682e4ea7-8030-43a9-9e1d-02564a2075cd/resolve/main/README.md
1.12 kB
metadata
library_name: peft
license: llama3.1
base_model: unsloth/Llama-3.1-Storm-8B
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 682e4ea7-8030-43a9-9e1d-02564a2075cd
results: []
682e4ea7-8030-43a9-9e1d-02564a2075cd
This model is a fine-tuned version of unsloth/Llama-3.1-Storm-8B on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.0864
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1