Instructions to use mrhunghd/e95dd472-c1b7-42fa-98ef-b20a4966521e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mrhunghd/e95dd472-c1b7-42fa-98ef-b20a4966521e with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("HuggingFaceH4/zephyr-7b-beta") model = PeftModel.from_pretrained(base_model, "mrhunghd/e95dd472-c1b7-42fa-98ef-b20a4966521e") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d5898901599ebea70a37d6f6d89c8e8922391ccc5870a315dba867a19e0f3dd2
- Size of remote file:
- 83.9 MB
- SHA256:
- 93edb491b62a8a9a03f02f5f7aca7fb986198ee21aef82ef2ab841b68da6409b
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