LoRA adapter release for the paper BTGenBot: Behavior Tree Generation for Robotic Tasks with Lightweight LLMs, currently in submission at IEEE/RSJ International Conference on Intelligent Robots and Systems.GitHub Repository
Paper
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Model Details
Model Description
- Developed by: Riccardo Andrea Izzo
- Model type: Transformer-based language model
- Language(s) (NLP): English
- Finetuned from model [optional]: CodeLlama-7b-Instruct-hf
Model Sources [optional]
- Repository: codellama/CodeLlama-7b-Instruct-hf
Uses
Behavior trees generation for robotic tasks
Hardware infrastructure
- Hardware Type: 2x NVIDIA Quadro RTX 6000
- Hours used: 36h
Training procedure
The following bitsandbytes
quantization config was used during training:
- quant_method: bitsandbytes
- load_in_8bit: True
- load_in_4bit: False
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: fp4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float32
Framework versions
- PEFT 0.6.0
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Base model
codellama/CodeLlama-7b-Instruct-hf