Text Classification
Transformers
PyTorch
TensorBoard
Bengali
bert
Generated from Trainer
text-embeddings-inference
Instructions to use ka05ar/bert-base-multilingual-cased-VITD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ka05ar/bert-base-multilingual-cased-VITD with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ka05ar/bert-base-multilingual-cased-VITD")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ka05ar/bert-base-multilingual-cased-VITD") model = AutoModelForSequenceClassification.from_pretrained("ka05ar/bert-base-multilingual-cased-VITD", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 1500
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 711495797
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:0d8c5c498b45db768cb680caa85f2746757c1e1a79f33ef42a7cb4f9879fcbbc
|
| 3 |
size 711495797
|
runs/Aug18_13-56-06_6c67123620d5/events.out.tfevents.1692366980.6c67123620d5.29.0
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:f857ef356dfa2e797f3ee02e0e0d5d83c28e2837e0b3d0ad3958feb339de3197
|
| 3 |
+
size 8646
|