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---
base_model: Qwen/Qwen2.5-7B-Instruct
library_name: peft
license: apache-2.0
datasets:
- medalpaca/medical_meadow_medical_flashcards
language:
- en
pipeline_tag: text-generation
---
# Model Card for FlowerTune-Qwen2.5-7B-Instruct-Medical-PEFT
This PEFT adapter has been trained by using [Flower](https://flower.ai/), a friendly federated AI framework.
The adapter and benchmark results have been submitted to the [FlowerTune LLM Medical Leaderboard](https://flower.ai/benchmarks/llm-leaderboard/medical/).
## Model Details
Please check the following GitHub project for model details and evaluation results:
[https://github.com/mrs83/FlowerTune-Qwen2.5-7B-Instruct-Medical](https://github.com/mrs83/FlowerTune-Qwen2.5-7B-Instruct-Medical)
## Training procedure
The following `bitsandbytes` quantization config was used during training:
- quant_method: bitsandbytes
- _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: fp4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float32
- bnb_4bit_quant_storage: uint8
- load_in_4bit: True
- load_in_8bit: False
### Framework versions
- PEFT 0.6.2
- Flower 1.12.0 |