Instructions to use havinash-ai/8a2cb479-c2de-4f1f-9d80-ef41fb2f5540 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use havinash-ai/8a2cb479-c2de-4f1f-9d80-ef41fb2f5540 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-2-2b-it") model = PeftModel.from_pretrained(base_model, "havinash-ai/8a2cb479-c2de-4f1f-9d80-ef41fb2f5540") - Notebooks
- Google Colab
- Kaggle
metadata
library_name: peft
license: gemma
base_model: unsloth/gemma-2-2b-it
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 8a2cb479-c2de-4f1f-9d80-ef41fb2f5540
results: []
8a2cb479-c2de-4f1f-9d80-ef41fb2f5540
This model is a fine-tuned version of unsloth/gemma-2-2b-it on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.1191
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