Instructions to use viswavi/datafinder-scibert-keyword-queries with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use viswavi/datafinder-scibert-keyword-queries with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="viswavi/datafinder-scibert-keyword-queries")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("viswavi/datafinder-scibert-keyword-queries") model = AutoModel.from_pretrained("viswavi/datafinder-scibert-keyword-queries") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
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:ae394611aff310941ceeaebf820a449fb393c8ba92829d14e1bfc669a6e19bf4
|
| 3 |
+
size 439700408
|