Instructions to use daniel40/4a2e8032-7e64-43a1-9e00-03b50c2ba878 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use daniel40/4a2e8032-7e64-43a1-9e00-03b50c2ba878 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("teknium/OpenHermes-2.5-Mistral-7B") model = PeftModel.from_pretrained(base_model, "daniel40/4a2e8032-7e64-43a1-9e00-03b50c2ba878") - Notebooks
- Google Colab
- Kaggle
4a2e8032-7e64-43a1-9e00-03b50c2ba878
This model is a fine-tuned version of teknium/OpenHermes-2.5-Mistral-7B on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.5672
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
- Downloads last month
- 2
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Model tree for daniel40/4a2e8032-7e64-43a1-9e00-03b50c2ba878
Base model
mistralai/Mistral-7B-v0.1 Finetuned
teknium/OpenHermes-2.5-Mistral-7B