Instructions to use cunghoctienganh/1aaac24d-e309-48ae-b933-de333fd89fab with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cunghoctienganh/1aaac24d-e309-48ae-b933-de333fd89fab with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("jhflow/mistral7b-lora-multi-turn-v2") model = PeftModel.from_pretrained(base_model, "cunghoctienganh/1aaac24d-e309-48ae-b933-de333fd89fab") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 002db052e70de3addd36af089fa4797a840331be698ffef3388dbd172fdec191
- Size of remote file:
- 6.78 kB
- SHA256:
- e45d2d3dba86aa936fff40512cce6d04741acbadb7fd6ca499ef8c8c7d7b4df4
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