Instructions to use castorini/bpr-nq-ctx-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use castorini/bpr-nq-ctx-encoder with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, DPRContextEncoder tokenizer = AutoTokenizer.from_pretrained("castorini/bpr-nq-ctx-encoder") model = DPRContextEncoder.from_pretrained("castorini/bpr-nq-ctx-encoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload pytorch_model.bin with git-lfs
Browse files- pytorch_model.bin +3 -0
pytorch_model.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:ff71c8828ff312ea197499d17332e30212983822badbd636fb1c00f2e8dca2ba
|
| 3 |
+
size 437995699
|