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 ·
5cb4519
1
Parent(s): 225e76a
update weights
Browse files- config.json +1 -1
- pytorch_model.bin +1 -1
- tf_model.h5 +1 -1
config.json
CHANGED
|
@@ -21,7 +21,7 @@
|
|
| 21 |
"num_groups": 1,
|
| 22 |
"num_hidden_layers": 12,
|
| 23 |
"pad_token_id": 0,
|
| 24 |
-
"transformers_version": "4.
|
| 25 |
"type_vocab_size": 2,
|
| 26 |
"vocab_size": 30522
|
| 27 |
}
|
|
|
|
| 21 |
"num_groups": 1,
|
| 22 |
"num_hidden_layers": 12,
|
| 23 |
"pad_token_id": 0,
|
| 24 |
+
"transformers_version": "4.4.0.dev0",
|
| 25 |
"type_vocab_size": 2,
|
| 26 |
"vocab_size": 30522
|
| 27 |
}
|
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 sha256:12c7e75e7372edda8fdb5d12925b0042267d8d8517fce8fb8a010422dc71cc35
|
| 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 423072408
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:5771e904639b7d9248e8df184dc8ea5831a41c0a381547c694199e1b8204ca28
|
| 3 |
size 423072408
|