Instructions to use phililp-arnold/7d2bd98e-c345-4e40-9da4-18823842abac with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use phililp-arnold/7d2bd98e-c345-4e40-9da4-18823842abac with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("garage-bAInd/Camel-Platypus2-70B") model = PeftModel.from_pretrained(base_model, "phililp-arnold/7d2bd98e-c345-4e40-9da4-18823842abac") - Notebooks
- Google Colab
- Kaggle
phililp-arnold/7d2bd98e-c345-4e40-9da4-18823842abac
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.0836
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 4.46.3
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3
- Downloads last month
- 3
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Model tree for phililp-arnold/7d2bd98e-c345-4e40-9da4-18823842abac
Base model
garage-bAInd/Camel-Platypus2-70B