Instructions to use tlam25/phase1_bert_undersampling_appearance with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tlam25/phase1_bert_undersampling_appearance with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tlam25/phase1_bert_undersampling_appearance")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tlam25/phase1_bert_undersampling_appearance") model = AutoModelForSequenceClassification.from_pretrained("tlam25/phase1_bert_undersampling_appearance") - Notebooks
- Google Colab
- Kaggle
Upload BertForSequenceClassification
Browse files- model.safetensors +1 -1
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 437958648
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:b6f4502046f7b6c8c3dd77352c871ada78a17fc8ea8cecebd33885d2b0d1b702
|
| 3 |
size 437958648
|