Instructions to use dibyendubiswas1998/llm-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dibyendubiswas1998/llm-test with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("TheBloke/Mistral-7B-Instruct-v0.1-GPTQ") model = PeftModel.from_pretrained(base_model, "dibyendubiswas1998/llm-test") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7ca8b8b7f96daef8c9c079f8d9198716620e0f85a92d8ace99daa93005cd6509
- Size of remote file:
- 27.3 MB
- SHA256:
- 9e17edade1141dec117885b92c6fc503d32f938de5219bcab4120d0250dc780d
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