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 rng_state.pth from MuhammedYahia/LLMSecurity350monoPython: direct link, hf CLI and curl.
- Browser
- Download file 14.2 kB
-
https://huggingface.co/MuhammedYahia/LLMSecurity350monoPython/resolve/main/rng_state.pth
- Command line
-
hf download hf://MuhammedYahia/LLMSecurity350monoPython/rng_state.pth
-
curl -L -o rng_state.pth https://huggingface.co/MuhammedYahia/LLMSecurity350monoPython/resolve/main/rng_state.pth
14.2 kB
- Xet hash:
- 1de870994318133ad84d3e53e366aee2e31447fe9facb3418ae31eabf644c726
- Size of remote file:
- 14.2 kB
- SHA256:
- a8f037b1bc0d160d86fab5da09aa2dd8683f9e916a04e84a2669baeda6833cce
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