Instructions to use mamung/b2e74748-c554-47db-9276-2b679fee7d9c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mamung/b2e74748-c554-47db-9276-2b679fee7d9c with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/tinyllama-chat") model = PeftModel.from_pretrained(base_model, "mamung/b2e74748-c554-47db-9276-2b679fee7d9c") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bec137b744739483db92cd6964809be81f50ebd6466acaf5a07d6e0d57cfeec9
- Size of remote file:
- 6.84 kB
- SHA256:
- 7f96e40d16be7b9d63f27a0024dd2277ac5846a1109931123716629609fceb1e
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