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--- |
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license: apache-2.0 |
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tags: |
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- llama |
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- llama-3 |
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- causal-lm |
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- lora |
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- fine-tuned |
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- peft |
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- syslog |
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- network packet |
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base_model: meta-llama/Meta-Llama-3-8B |
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model_type: llama |
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--- |
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# LlamaTrace (Merged LoRA + Base) |
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## Model Information |
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- **Base Model**: `meta-llama/Meta-Llama-3-8B` |
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- **Fine-tuning Method**: LoRA (Low-Rank Adaptation) |
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- **Training Objective**: Network traffic analysis, anomaly detection, syslog/pcap summarization |
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- **Tokenizer**: base model tokenizer |
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## How to use |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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model = AutoModelForCausalLM.from_pretrained("choihyuunmin/LLaMa-PcapLog") |
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tokenizer = AutoTokenizer.from_pretrained("choihyuunmin/LLaMa-PcapLog") |
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input_text = "Anaylze below network packet : \n" |
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inputs = tokenizer(input_text, return_tensors="pt") |
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outputs = model.generate(**inputs, max_new_tokens=128) |
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print(tokenizer.decode(outputs[0], skip_special_tokens=True)) |
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