Instructions to use tahamajs/plamma with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use tahamajs/plamma with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/paligemma-3b-pt-224") model = PeftModel.from_pretrained(base_model, "tahamajs/plamma") - Notebooks
- Google Colab
- Kaggle
Download quantized_model.pth from tahamajs/plamma: direct link, hf CLI and curl.
- Browser
- Download file 3.46 GB
-
https://huggingface.co/tahamajs/plamma/resolve/main/quantized_model.pth
- Command line
-
hf download hf://tahamajs/plamma/quantized_model.pth
-
curl -L -o quantized_model.pth https://huggingface.co/tahamajs/plamma/resolve/main/quantized_model.pth
3.46 GB
- Xet hash:
- 62536516e2415e6f4f6a316e97be01d7f8e54ec7f12b8a8145524925291cc4d3
- Size of remote file:
- 3.46 GB
- SHA256:
- 22534cb06fdced572666e4e09a3d607add107ae12f899f6a22132e2d1e6d9859
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