Instructions to use helling100/Regression_albert_4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use helling100/Regression_albert_4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="helling100/Regression_albert_4")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("helling100/Regression_albert_4") model = AutoModelForSequenceClassification.from_pretrained("helling100/Regression_albert_4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
d28af03
1
Parent(s): 0f7e60d
Training in progress, epoch 4
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 46751109
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:5cc4fdfa12c45c50e2652197bd8c809aa2c975196e52918a8e738338c642bb2a
|
| 3 |
size 46751109
|
runs/Mar22_12-54-33_a5f6d9252c7d/events.out.tfevents.1679489889.a5f6d9252c7d.141.0
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 sha256:93794bc7585dda7fb14b3457fccb9737d939622a0caa091256ffb417398a96f7
|
| 3 |
+
size 5976
|