Instructions to use lucky-verma/sleep-llm-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use lucky-verma/sleep-llm-model with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/mistral-7b-v0.3-bnb-4bit") model = PeftModel.from_pretrained(base_model, "lucky-verma/sleep-llm-model") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from lucky-verma/sleep-llm-model: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/lucky-verma/sleep-llm-model/resolve/main/training_args.bin
- Command line
-
hf download hf://lucky-verma/sleep-llm-model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/lucky-verma/sleep-llm-model/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- 8e442cf9397367afd2b9ad218ab86d1cbb5a0b7ffdac2743f90b497dfc3dadf6
- Size of remote file:
- 5.11 kB
- SHA256:
- 3d8a8aae68e9e22919416b0f577e24fc753fe8cbc425040903873cbc21df619a
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