Instructions to use NimaKL/spamd_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NimaKL/spamd_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NimaKL/spamd_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NimaKL/spamd_model") model = AutoModelForSequenceClassification.from_pretrained("NimaKL/spamd_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +1 -0
config.json
CHANGED
|
@@ -24,3 +24,4 @@
|
|
| 24 |
"use_cache": true,
|
| 25 |
"vocab_size": 32000
|
| 26 |
}
|
|
|
|
|
|
| 24 |
"use_cache": true,
|
| 25 |
"vocab_size": 32000
|
| 26 |
}
|
| 27 |
+
|