Text Classification
Transformers
PyTorch
Safetensors
English
bert
text classification
text-embeddings-inference
Instructions to use sarahmiller137/bioclinical-bert-ft-m3-lc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sarahmiller137/bioclinical-bert-ft-m3-lc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sarahmiller137/bioclinical-bert-ft-m3-lc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sarahmiller137/bioclinical-bert-ft-m3-lc") model = AutoModelForSequenceClassification.from_pretrained("sarahmiller137/bioclinical-bert-ft-m3-lc") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6850c601d908fb6b9b6164104fab734bebb99316b53b1745eaad11da1ee8ede3
- Size of remote file:
- 433 MB
- SHA256:
- e9d7e509b614af68949bfc6c4f80f1b2178e5f09f4f55fd801eae504c6820997
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