Instructions to use DevQuasar/llama3.1_8b_chat_brainstorm-v3.1_adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use DevQuasar/llama3.1_8b_chat_brainstorm-v3.1_adapter with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3.1-8B") model = PeftModel.from_pretrained(base_model, "DevQuasar/llama3.1_8b_chat_brainstorm-v3.1_adapter") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 88c1fba1735d02f97186e84c2dada92052495f0d1df4c9731a49845fe29f6c9e
- Size of remote file:
- 5.18 kB
- SHA256:
- 6cb864042de7830fc6897c05883901045209dbad6ac3e0901065ce5c0c755d02
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