Instructions to use bunnycore/Llama-3.2-3b-RRP-lora_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bunnycore/Llama-3.2-3b-RRP-lora_model with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("bunnycore/Llama-3.2-3b-RRP-lora_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
metadata
base_model: unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
license: apache-2.0
language:
- en
datasets:
- Nitral-AI/Discover-Intstruct-6k-Distilled-R1-70b-ShareGPT
dataset = load_dataset("NovaSky-AI/Sky-T1_data_17k", split="train")
dataset2 = load_dataset("Nitral-AI/Discover-Intstruct-6k-Distilled-R1-70b-ShareGPT", split="train")
dataset3 = load_dataset("Nitral-Archive/RP_Alignment-ShareGPT", split="train")
dataset4 = load_dataset("alexandreteles/AlpacaToxicQA_ShareGPT", split="train")
Uploaded model
- Developed by: bunnycore
- License: apache-2.0
- Finetuned from model : unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
