Instructions to use navidmadani/esconv_sra_llama3_8b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use navidmadani/esconv_sra_llama3_8b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.1-8B-Instruct") model = PeftModel.from_pretrained(base_model, "navidmadani/esconv_sra_llama3_8b") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ff0bc722b7a1f84435c2b44f8c478b7b94dae2276be6136ba713827ea7bdc77a
- Size of remote file:
- 5.5 kB
- SHA256:
- 80a7c0a82fae4149ea7504c4c5260cf29734952348066095a6a53c257204bee9
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