Instructions to use ncbi/MedCPT-Cross-Encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ncbi/MedCPT-Cross-Encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ncbi/MedCPT-Cross-Encoder")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ncbi/MedCPT-Cross-Encoder") model = AutoModelForSequenceClassification.from_pretrained("ncbi/MedCPT-Cross-Encoder") - Inference
- Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:b27e15c8bae944cb3cfd752e09669e447bd6282f787115ee485b484ef4657eb9
|
| 3 |
+
size 437955572
|