Instructions to use nlpie/bio-mobilebert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nlpie/bio-mobilebert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nlpie/bio-mobilebert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("nlpie/bio-mobilebert") model = AutoModelForMaskedLM.from_pretrained("nlpie/bio-mobilebert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Mojtaba aka Omid Rohanian commited on
Commit ·
fa386ab
1
Parent(s): b420287
Second version of the BioMobileBERT model.
Browse files- config.json +1 -1
- pytorch_model.bin +1 -1
config.json
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{
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"_name_or_path": "distil-biobert/models/bio-mobilebert/final/model-
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"architectures": [
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"MobileBertForMaskedLM"
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],
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{
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"_name_or_path": "distil-biobert/models/bio-mobilebert/final/model-120k",
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"architectures": [
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"MobileBertForMaskedLM"
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],
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:e746beab86bdc61b048222664d77b67f3a52e2b927715d815fb250edeaf3cb35
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size 146842235
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