Instructions to use dtorber/bert-base-cased_K1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dtorber/bert-base-cased_K1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dtorber/bert-base-cased_K1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dtorber/bert-base-cased_K1") model = AutoModelForSequenceClassification.from_pretrained("dtorber/bert-base-cased_K1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 9
Browse files
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 433270768
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:10c00ecc4eab330881087707d85d27c01661cf682e792c061a78f660fb248e44
|
| 3 |
size 433270768
|
runs/Mar12_14-10-53_tardis/events.out.tfevents.1710249055.tardis.125084.0
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 sha256:03bc46ccd2fd058121fdcf30c447b9b24c9e885635c09d60ad437f16b6f93841
|
| 3 |
+
size 5715
|