Instructions to use YituTech/conv-bert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YituTech/conv-bert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="YituTech/conv-bert-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("YituTech/conv-bert-base") model = AutoModel.from_pretrained("YituTech/conv-bert-base") - Inference
- Notebooks
- Google Colab
- Kaggle
Abhishek Thakur commited on
Commit ·
3abdc6f
1
Parent(s): 64c19bc
update models
Browse files- pytorch_model.bin +1 -1
- tf_model.h5 +1 -1
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 422840281
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:57adad75240332ce19574838f9893ea3ba330cdd6a06c142ccfd3e3ae3cf6079
|
| 3 |
size 422840281
|
tf_model.h5
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 423072720
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:304aca3eab4ec5db544ae29058877d25605ab9223a8299feb3b7acd5c8cf1691
|
| 3 |
size 423072720
|