Instructions to use JunHwi/p_encoder_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JunHwi/p_encoder_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="JunHwi/p_encoder_test")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("JunHwi/p_encoder_test") model = AutoModelForMaskedLM.from_pretrained("JunHwi/p_encoder_test") - Notebooks
- Google Colab
- Kaggle
p_encoder!
Browse files- passage_encoder.pt +3 -0
passage_encoder.pt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:9fc64eb062099d456ef16a0f5e14706e1d1a2e42ed207a890981e3bbfe06c3f1
|
| 3 |
+
size 442558967
|