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
| { | |
| "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" | |
| } | |