mirror of
https://github.com/Shiva108/ai-llm-red-team-handbook.git
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b3d3bac51f
- Extracted all code examples from handbook chapters - Organized into 15 attack categories - Created shared utilities (api_client, validators, logging, constants) - Added workflow orchestration scripts - Implemented install.sh for easy setup - Renamed all scripts to descriptive functional names - Added comprehensive README and documentation - Included pytest test suite and configuration
37 lines
837 B
Python
37 lines
837 B
Python
#!/usr/bin/env python3
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"""
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9.5 Practical Inspection: Loading a Model
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Source: Chapter_09_LLM_Architectures_and_System_Components
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Category: utils
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"""
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from transformers import AutoModelForCausalLM
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import torch
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import argparse
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import sys
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# Load model (use 4-bit quantization for consumer GPUs)
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model = AutoModelForCausalLM.from_pretrained(
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"mistralai/Mistral-7B-v0.1",
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device_map="auto",
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load_in_4bit=True
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)
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# Inspect Configuration
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# Look for 'max_position_embeddings' (Context Window size)
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print(model.config)
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def main():
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"""Command-line interface."""
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parser = argparse.ArgumentParser(description=__doc__)
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parser.add_argument("--verbose", "-v", action="store_true", help="Verbose output")
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args = parser.parse_args()
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# TODO: Add main execution logic
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pass
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if __name__ == "__main__":
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main() |