Instructions to use dimasik2987/9f20610d-d76f-414d-9e50-134be458ed3e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dimasik2987/9f20610d-d76f-414d-9e50-134be458ed3e 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, "dimasik2987/9f20610d-d76f-414d-9e50-134be458ed3e") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e119a80641a6f03500c893ba0160638f26ea744ae2f6030d8fe8faaf9d8a1042
- Size of remote file:
- 6.71 kB
- SHA256:
- 93bdcc251160812511bba44b5dafa17c01a796001143d2415012295633647707
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