Instructions to use petra345/MyAwesomeModel-BalancedGate with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use petra345/MyAwesomeModel-BalancedGate with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="petra345/MyAwesomeModel-BalancedGate")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("petra345/MyAwesomeModel-BalancedGate") model = AutoModelForSequenceClassification.from_pretrained("petra345/MyAwesomeModel-BalancedGate", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Release balanced gate checkpoint cobalt_0510
Browse files- pytorch_model.bin +1 -3
pytorch_model.bin
CHANGED
|
@@ -1,3 +1 @@
|
|
| 1 |
-
|
| 2 |
-
oid sha256:0722f298fe8b8a7648b1a68e882f5db7674c4255475d8876f18ea5f5b42454c3
|
| 3 |
-
size 37
|
|
|
|
| 1 |
+
cobalt_0510 balanced release payload
|
|
|
|
|
|