Instructions to use beast33/3bb082f8-9b97-4ea9-909c-13d0c56da196 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use beast33/3bb082f8-9b97-4ea9-909c-13d0c56da196 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("scb10x/llama-3-typhoon-v1.5-8b-instruct") model = PeftModel.from_pretrained(base_model, "beast33/3bb082f8-9b97-4ea9-909c-13d0c56da196") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3c03e9f72c299f65c678c1b728eb93f15523e9407d5d83eb300883d976a0fe56
- Size of remote file:
- 84 MB
- SHA256:
- 053499e1873494c55e4f56cb4d40b9cd5afa202221d1b271de5b2810cd1969bf
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