Fill-Mask
Transformers
PyTorch
JAX
English
bert
exbert
medical
biomedical-nlp
pubmed
literature-mining
drug-discovery
aurigene
Instructions to use Aurigene-AI/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Aurigene-AI/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Aurigene-AI/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Aurigene-AI/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext") model = AutoModelForMaskedLM.from_pretrained("Aurigene-AI/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add Aurigene AI mirror header, discovery-stage context and catalogue tags
Browse files
README.md
CHANGED
|
@@ -2,9 +2,29 @@
|
|
| 2 |
language: en
|
| 3 |
tags:
|
| 4 |
- exbert
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 5 |
license: mit
|
| 6 |
widget:
|
| 7 |
-
- text:
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 8 |
---
|
| 9 |
|
| 10 |
## MSR BiomedBERT (abstracts + full text)
|
|
|
|
| 2 |
language: en
|
| 3 |
tags:
|
| 4 |
- exbert
|
| 5 |
+
- medical
|
| 6 |
+
- biomedical-nlp
|
| 7 |
+
- pubmed
|
| 8 |
+
- literature-mining
|
| 9 |
+
- drug-discovery
|
| 10 |
+
- aurigene
|
| 11 |
license: mit
|
| 12 |
widget:
|
| 13 |
+
- text: '[MASK] is a tumor suppressor gene.'
|
| 14 |
+
pipeline_tag: fill-mask
|
| 15 |
+
library_name: transformers
|
| 16 |
+
---
|
| 17 |
+
|
| 18 |
+
<!-- aurigene-header -->
|
| 19 |
+
> ### Mirrored by [Aurigene AI](https://huggingface.co/Aurigene-AI)
|
| 20 |
+
> **Discovery stage:** Evidence and literature
|
| 21 |
+
>
|
| 22 |
+
> Microsoft BiomedBERT (PubMedBERT), pretrained from scratch on PubMed abstracts plus PMC full text. The standard encoder backbone for biomedical NER and relation extraction.
|
| 23 |
+
>
|
| 24 |
+
> Upstream: [`microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext`](https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext) - all credit to the original authors; the model card and licence below are theirs.
|
| 25 |
+
>
|
| 26 |
+
> Explore the rest of the catalogue: [Molecule Explorer](https://huggingface.co/spaces/Aurigene-AI/molecule-explorer) - [Protein Target Explorer](https://huggingface.co/spaces/Aurigene-AI/protein-target-explorer) - [Drug Discovery Model Hub](https://huggingface.co/spaces/Aurigene-AI/drug-discovery-model-hub)
|
| 27 |
+
|
| 28 |
---
|
| 29 |
|
| 30 |
## MSR BiomedBERT (abstracts + full text)
|