Instructions to use Cameron/BERT-eec-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cameron/BERT-eec-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cameron/BERT-eec-emotion")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cameron/BERT-eec-emotion") model = AutoModelForSequenceClassification.from_pretrained("Cameron/BERT-eec-emotion") - Notebooks
- Google Colab
- Kaggle
Commit ·
2fc079c
1
Parent(s): f08c4e4
upload flax model
Browse files- flax_model.msgpack +3 -0
flax_model.msgpack
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:b7dc203a098abfb74e1e9e939afac7261637ad0173bc3d921a23b0ea5c05741b
|
| 3 |
+
size 433263684
|