Bio-SIEVE-Multi

Bio-SIEVE-Multi

Arxiv Github

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.

Also see the single-task variant for more performative Inclusion/Exclusion classification. Variants trained without instruction tuned pretraining TBD.

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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