Instructions to use NeeruAjith/SpiderFiberProp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use NeeruAjith/SpiderFiberProp with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NeeruAjith/SpiderSeqGen") model = PeftModel.from_pretrained(base_model, "NeeruAjith/SpiderFiberProp") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-2500/optimizer.pt from NeeruAjith/SpiderFiberProp: direct link, hf CLI and curl.
- Browser
- Download file 6.31 MB
-
https://huggingface.co/NeeruAjith/SpiderFiberProp/resolve/main/checkpoint-2500/optimizer.pt
- Command line
-
hf download hf://NeeruAjith/SpiderFiberProp/checkpoint-2500/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/NeeruAjith/SpiderFiberProp/resolve/main/checkpoint-2500/optimizer.pt
6.31 MB
- Xet hash:
- b1dda5a30dbb27ab778299cffbdb112640502043d5fbf78553d6a2dd20e3284e
- Size of remote file:
- 6.31 MB
- SHA256:
- 8a2aa8d3d5431fe1917fa17e401b49e4b59d31fb095625d110bc333d3214172b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.