Instructions to use MuhammedYahia/LLMSecurity350monoPython with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use MuhammedYahia/LLMSecurity350monoPython with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Salesforce/codegen-350M-mono") model = PeftModel.from_pretrained(base_model, "MuhammedYahia/LLMSecurity350monoPython") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from MuhammedYahia/LLMSecurity350monoPython: direct link, hf CLI and curl.
- Browser
- Download file 196 MB
-
https://huggingface.co/MuhammedYahia/LLMSecurity350monoPython/resolve/main/optimizer.pt
- Command line
-
hf download hf://MuhammedYahia/LLMSecurity350monoPython/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/MuhammedYahia/LLMSecurity350monoPython/resolve/main/optimizer.pt
196 MB
- Xet hash:
- 67971f168e38bb3338e17c4ab8716673e72c979e71eadc6cd9aaba1021ad00dc
- Size of remote file:
- 196 MB
- SHA256:
- 13e53dd1b6bf9b97fa8657fe76f43c33b02003925b116dac3f71ef422dbb1f83
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