Instructions to use DevQuasar/llama3.2_3b_chat_brainstorm-v3.2.3_adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use DevQuasar/llama3.2_3b_chat_brainstorm-v3.2.3_adapter with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.2-3B") model = PeftModel.from_pretrained(base_model, "DevQuasar/llama3.2_3b_chat_brainstorm-v3.2.3_adapter") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6c5da56c20bbcffa4cef44e20335b433d146e3cd91af4557227c0729de1d8055
- Size of remote file:
- 5.3 kB
- SHA256:
- 26be913f1942640714387d7f61789ee9b243a28d4a568ffeae9a77985b566690
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