Instructions to use JeswinMS4/scam-alert-mobile-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JeswinMS4/scam-alert-mobile-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JeswinMS4/scam-alert-mobile-bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JeswinMS4/scam-alert-mobile-bert") model = AutoModelForSequenceClassification.from_pretrained("JeswinMS4/scam-alert-mobile-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 2900
Browse files
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 98470112
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:bf1ca108e44f53600bfe72019a4ffb5667322ee1b5b26ce380d12f97cb20de70
|
| 3 |
size 98470112
|
runs/Jun04_18-25-57_439968c1e8e4/events.out.tfevents.1717525558.439968c1e8e4.315.0
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:a40071ceb1b8fa280962ea27f09375ad13afeb0c6609c6ef25c2a1883ff246dd
|
| 3 |
+
size 16098
|