Instructions to use sukara13/gemma7bcars512 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use sukara13/gemma7bcars512 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-7b-it") model = PeftModel.from_pretrained(base_model, "sukara13/gemma7bcars512") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from sukara13/gemma7bcars512: direct link, hf CLI and curl.
- Browser
- Download file 14.6 MB
-
https://huggingface.co/sukara13/gemma7bcars512/resolve/main/optimizer.pt
- Command line
-
hf download hf://sukara13/gemma7bcars512/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/sukara13/gemma7bcars512/resolve/main/optimizer.pt
14.6 MB
- Xet hash:
- f0fe3bf20f36045fdc8a40521d96b02312142622ad417e0c1cb189302a65b758
- Size of remote file:
- 14.6 MB
- SHA256:
- b240303efbaebfe795f38db586d2ee69f76957737ddf17a6117d8eeeed860935
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