LlamaTrace (Merged LoRA + Base)
Model Information
- Base Model:
meta-llama/Meta-Llama-3-8B - Fine-tuning Method: LoRA (Low-Rank Adaptation)
- Training Objective: Network traffic analysis, anomaly detection, syslog/pcap summarization
- Tokenizer: base model tokenizer
How to use
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("choihyuunmin/LLaMa-PcapLog")
tokenizer = AutoTokenizer.from_pretrained("choihyuunmin/LLaMa-PcapLog")
input_text = "Anaylze below network packet : \n"
inputs = tokenizer(input_text, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=128)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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