Instructions to use havinash-ai/3cbee2fe-6e5f-43d7-93eb-21377bdf07ce with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use havinash-ai/3cbee2fe-6e5f-43d7-93eb-21377bdf07ce with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-2-2b-it") model = PeftModel.from_pretrained(base_model, "havinash-ai/3cbee2fe-6e5f-43d7-93eb-21377bdf07ce") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/optimizer.pt from havinash-ai/3cbee2fe-6e5f-43d7-93eb-21377bdf07ce: direct link, hf CLI and curl.
- Browser
- Download file 21.5 MB
-
https://huggingface.co/havinash-ai/3cbee2fe-6e5f-43d7-93eb-21377bdf07ce/resolve/4721b236b8ff08f28837c157c44bf3e625d3767f/last-checkpoint/optimizer.pt
- Command line
-
hf download hf://havinash-ai/3cbee2fe-6e5f-43d7-93eb-21377bdf07ce@4721b236b8ff08f28837c157c44bf3e625d3767f/last-checkpoint/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/havinash-ai/3cbee2fe-6e5f-43d7-93eb-21377bdf07ce/resolve/4721b236b8ff08f28837c157c44bf3e625d3767f/last-checkpoint/optimizer.pt
21.5 MB
- Xet hash:
- 5249e480e2f579c5ef73816fad641e24fd47a4549c5503ecb412ade0af525af1
- Size of remote file:
- 21.5 MB
- SHA256:
- 36159a5834d3137ffce518a2daa944dedbc7d631dcd8c5ab38dbaf5bc9d0587a
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