# Bio-SIEVE-Multi
[Arxiv](https://arxiv.org/abs/2308.06610) [Github](https://github.com/GateNLP/Bio-SIEVE)

The multi-task Bio-SIEVE trained for Inclusion/Exclusion classification of biomedical literature given the systematic review's objectives and selection criteria as well as exclusion reasoning and PIO Extraction.

These are LoRA weights, having continued training from Guanaco7B. The base LLaMA model will be automatically downloaded when used with the generate_cli.py script from our [Github](https://github.com/GateNLP/Bio-SIEVE).

Also see the [single-task variant](https://huggingface.co/GateNLP/Bio-SIEVE) for more performative Inclusion/Exclusion classification. Variants trained without instruction tuned pretraining TBD.


---
library_name: peft
---
## Training procedure


The following `bitsandbytes` quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- 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: nf4
- bnb_4bit_use_double_quant: True
- bnb_4bit_compute_dtype: float32

The following `bitsandbytes` quantization config was used during training:
- load_in_8bit: False
- load_in_4bit: True
- 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: nf4
- bnb_4bit_use_double_quant: True
- bnb_4bit_compute_dtype: float32
### Framework versions

- PEFT 0.4.0.dev0

- PEFT 0.4.0.dev0