Instructions to use erikacardenas300/StartupClassifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use erikacardenas300/StartupClassifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="erikacardenas300/StartupClassifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("erikacardenas300/StartupClassifier") model = AutoModelForSequenceClassification.from_pretrained("erikacardenas300/StartupClassifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
0078b2b
1
Parent(s): 4276c5d
Update config.json
Browse files- config.json +4 -0
config.json
CHANGED
|
@@ -4,6 +4,10 @@
|
|
| 4 |
"architectures": [
|
| 5 |
"DistilBertForSequenceClassification"
|
| 6 |
],
|
|
|
|
|
|
|
|
|
|
|
|
|
| 7 |
"attention_dropout": 0.1,
|
| 8 |
"dim": 768,
|
| 9 |
"dropout": 0.1,
|
|
|
|
| 4 |
"architectures": [
|
| 5 |
"DistilBertForSequenceClassification"
|
| 6 |
],
|
| 7 |
+
"label2id": {
|
| 8 |
+
"0": "finance",
|
| 9 |
+
"1": "biotechnology",
|
| 10 |
+
},
|
| 11 |
"attention_dropout": 0.1,
|
| 12 |
"dim": 768,
|
| 13 |
"dropout": 0.1,
|