Instructions to use theCuiCoders/bert-base-uncased-FinedTuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use theCuiCoders/bert-base-uncased-FinedTuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="theCuiCoders/bert-base-uncased-FinedTuned")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("theCuiCoders/bert-base-uncased-FinedTuned") model = AutoModelForSequenceClassification.from_pretrained("theCuiCoders/bert-base-uncased-FinedTuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 8000
Browse files
events.out.tfevents.1719935722.68005939a7c4.1503.0
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:fa4c4b528f29750a9dafa92f3e65ceb22f4bb38415d27c8b9e08f69b0a66a2b7
|
| 3 |
+
size 76437
|
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 437955572
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:9ccd2720b61b704aadb2734f8af6eb9bfac1b4f9d2afaafe498626351bfca45b
|
| 3 |
size 437955572
|