Text Generation
PEFT
Safetensors
English
security
cybersecurity
lora
mistral
fine-tuned
instruction-tuned
conversational
Instructions to use debashis2007/security-mistral-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use debashis2007/security-mistral-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.1") model = PeftModel.from_pretrained(base_model, "debashis2007/security-mistral-lora") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from debashis2007/security-mistral-lora: direct link, hf CLI and curl.
- Browser
- Download file 3.51 MB
-
https://huggingface.co/debashis2007/security-mistral-lora/resolve/main/tokenizer.json
- Command line
-
hf download hf://debashis2007/security-mistral-lora/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/debashis2007/security-mistral-lora/resolve/main/tokenizer.json
3.51 MB
File too large to display, you can check the raw version instead.