Instructions to use dzanbek/dcef9753-f7f8-4e09-92b6-472a529277fb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dzanbek/dcef9753-f7f8-4e09-92b6-472a529277fb with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Nous-Hermes-llama-2-7b") model = PeftModel.from_pretrained(base_model, "dzanbek/dcef9753-f7f8-4e09-92b6-472a529277fb") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2437fcd9c2e5d2c6a0afd89573eca85820fa222b339f2a428cc0de6757560b82
- Size of remote file:
- 6.78 kB
- SHA256:
- caed7626109b94767dacc0e997c36b759df4ca2ae0a19be1547c689c92fce1e2
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