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--- |
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language: en |
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tags: |
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- snomed-ct |
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- text-generation |
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--- |
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# My Model Name |
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## Model description |
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This is a text generation model for SNOMED-CT. As it is text-generation, it is prone to hallucination and should not be used for any kind of production purpose but it was fun to build. It is based on Mixtral7b and was fine-tuned on a part of the SNOMED-CT corpus then tested against a gold-standard. |
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## How to use |
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Provide code snippets on how to use your model. |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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model_name = "MattStammers/chatty_mapper" |
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model = AutoModelForCausalLM.from_pretrained(model_name) |
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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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# Your example here |
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Model Performance |
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Accuracy: 0.0 |
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Precision: 0.0 |
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Recall: 0.0 |
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Example DataFrame head: ParameterName SNOMEDCode \ |
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0 *Heart rate 364075005 |
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1 Peripheral oxygen saturation 431314004 |
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2 Mean arterial pressure 1285244000 |
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3 *Diastolic blood pressure 271650006 |
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4 *Systolic blood pressure 271649006 |
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ExtractedSNOMEDNumbers CorrectPrediction |
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0 3222222 False |
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1 4222222000000000000000000000000000000000000000... False |
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2 NaN False |
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3 NaN False |
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4 NaN False |
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Limitations and bias |
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It is prone to wandering and certainly not medical-grade. |
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Acknowledgments |
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Thanks to the Mixtral AI team for creating the base model. |
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``` |
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Save the model card in the model directory |
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with open(f"models/chatty_mapper/README.md", "w") as f: |
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f.write(model_card_content) |
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Use Hugging Face's Repository class for Git operations |
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repo = Repository(local_dir=model_save_path, clone_from=repo_url) |
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repo.git_add() |
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repo.git_commit("Initial model upload with model card and metrics") |
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repo.git_push() |
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print(f"Model, model card, and metrics successfully pushed to: https://huggingface.co/MattStammers/chatty_mapper") |
