Instructions to use monsterapi/gemma-2b-lora-maths-orca-200k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use monsterapi/gemma-2b-lora-maths-orca-200k with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-2b") model = PeftModel.from_pretrained(base_model, "monsterapi/gemma-2b-lora-maths-orca-200k") - Notebooks
- Google Colab
- Kaggle
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- Notably, it **outperformed larger models like LLaMA-2-13B and Code-LLaMA-7B**
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This result suggests that targeted fine-tuning can significantly improve model performance.
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- Notably, it **outperformed larger models like LLaMA-2-13B and Code-LLaMA-7B**
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This result suggests that targeted fine-tuning can significantly improve model performance.
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### Read the Detailed Case Study over [here](https://blog.monsterapi.ai/finetuned-gemma-2b-on-monsterapi-outperforms-llama-13b/)
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