Instructions to use kfallah/Llama-3.2-1B-Instruct-DPO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use kfallah/Llama-3.2-1B-Instruct-DPO with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.2-1B-Instruct") model = PeftModel.from_pretrained(base_model, "kfallah/Llama-3.2-1B-Instruct-DPO") - Notebooks
- Google Colab
- Kaggle
Gated model You can list files but not access them
Preview of files found in this repository
- 16lora_fp16_1b_lr1e-6
- 32lora_fp16_1b_lr1e-6
- 32lora_fp16_1b_lr5e-6
- Llama-3.2-1B-Instruct-DPO-LoRA-r16-8bit
- checkpoint-1000
- checkpoint-1500
- checkpoint-200
- checkpoint-2000
- checkpoint-500
- llama-1b-dpo-e2e
- 1.9 kB
- 5.11 kB
- 727 Bytes
- 3.42 MB xet
- 1.81 MB xet
- 14.2 kB xet
- 1.06 kB xet
- 325 Bytes
- 17.2 MB xet
- 54.6 kB
- 107 kB
- 6.2 kB xet