Instructions to use toolathlonEval/FilteredBert-EvalRepo-358 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use toolathlonEval/FilteredBert-EvalRepo-358 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="toolathlonEval/FilteredBert-EvalRepo-358")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("toolathlonEval/FilteredBert-EvalRepo-358") model = AutoModelForSequenceClassification.from_pretrained("toolathlonEval/FilteredBert-EvalRepo-358", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 314 Bytes
fa2114e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"model_type": "bert",
"architectures": [
"BertForSequenceClassification"
],
"hidden_size": 768,
"num_hidden_layers": 12,
"training_step": 800,
"training_seed": 358,
"pipeline_tag": "text-classification",
"library_name": "transformers",
"selection_policy": "validated-apache-under-110m"
}
|