Comments (2)
Hi @carvalhoek,
I believe for this code we downloaded the model locally and ran it using the Hugging Face API. Given that this was a model and feature extractor made by another party, we do not have control on its distribution and support. What you can do is to change the code in your fork to implement and analogous model (https://huggingface.co/dmis-lab/biobert-v1.1).
You could do it like this (in the relevant code section):
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("dmis-lab/biobert-v1.1")
model = AutoModel.from_pretrained("dmis-lab/biobert-v1.1")
Happy coding,
--lrsoenksen
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Thanks man, that seems to solve it =)
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Related Issues (16)
- Value of `fname` in `2_3-Pathology Diagnosis Modeling.py` (and also other files) HOT 1
- Request for extracted dataset
- Missing file HOT 3
- Input window for time-series data HOT 4
- Number of training samples HOT 7
- How to use when missing files HOT 9
- Experiments results HOT 1
- Can't locate file HOT 2
- Definitions of records HOT 2
- Some files in the repo are missing in MIMIC datasets? HOT 3
- Patient vs Admission level aggregation
- get_chartevent_tsfresh_timeseries_embeddings has not been called
- Could not find "AUPRC_All_Modality_Resources. csv" HOT 1
- Broken embeddings file on PhysioNet?
- Tensorflow can removed from the requirements
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