Instructions to use bibekaryal/albert-base-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bibekaryal/albert-base-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bibekaryal/albert-base-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bibekaryal/albert-base-v2") model = AutoModelForSequenceClassification.from_pretrained("bibekaryal/albert-base-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:277f829539b06337a8a046178782050fe9f2a1a5c4d9525209a2ac5bd4604143
|
| 3 |
+
size 46760400
|