Instructions to use 5ivatej/Liquid-LFM-1.2B-Medical-Doctor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use 5ivatej/Liquid-LFM-1.2B-Medical-Doctor with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("LiquidAI/LFM2.5-1.2B-Instruct") model = PeftModel.from_pretrained(base_model, "5ivatej/Liquid-LFM-1.2B-Medical-Doctor") - Notebooks
- Google Colab
- Kaggle
Upload model
Browse files- README.md +4 -3
- adapter_config.json +3 -3
README.md
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@@ -13,9 +13,10 @@ language:
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- en
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widget:
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- text: "Patient: I have a sharp pain in my chest when I breathe deep. \nDoctor Assessment:"
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example_title:
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- text: "Patient: My child has a fever of 102 and a rash on the stomach. \nDoctor
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---
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# 🩺 Liquid-LFM-1.2B-Medical-Doctor
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- en
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widget:
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- text: "Patient: I have a sharp pain in my chest when I breathe deep. \nDoctor Assessment:"
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example_title: Chest Pain
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- text: "Patient: My child has a fever of 102 and a rash on the stomach. \nDoctor\
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\ Assessment:"
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example_title: Pediatric Fever
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---
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# 🩺 Liquid-LFM-1.2B-Medical-Doctor
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adapter_config.json
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"
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"q_proj",
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"down_proj",
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"up_proj",
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"gate_proj",
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"
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],
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"target_parameters": null,
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"task_type": "CAUSAL_LM",
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"v_proj",
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"q_proj",
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"up_proj",
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"o_proj",
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"gate_proj",
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"down_proj"
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],
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"target_parameters": null,
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"task_type": "CAUSAL_LM",
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