FireAct Llama-2/CodeLlama
FireAct Llama/CodeLlama is a collection of fine-tuned generative text models for performing ReAct with external search tools. Links to other models can be found in the Index section.
Foundation Model Details
Note: As the foundation models, Llama-2 and CodeLlama, are developed by Meta, please also read the guidance and license on their website, Llama-2 and CodeLlama, before using FireAct models.
Model Developers System 2 Research, Cambridge LTL, Monash University, Princeton PLI.
Variations FireAct models including Llama-2-7B full fine-tuned models, and Llama-2-[7B,13B], CodeLlama-[7B,13B,34B] LoRA fine-tuned models. All released models are fine-tuned on multi-task (HotpotQA/StrategyQA/MMLU) and multi-type (ReAct/CoT/Reflexion) data.
Input Models input text only.
Output Models generate text only.
Index
Full Fine-tuned Model
FireAct Llama-2:
LoRA Fine-tuned Model
FireAct Llama-2:
FireAct CodeLlama:
LoRA Training procedure
The following bitsandbytes quantization config was used during training:
- 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
