Text Classification
Grok
English
distilbert
mcp
tool-calling
qa-testing
error-detection
Eval Results (legacy)
Instructions to use brijeshvadi/mcp-error-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Grok
How to use brijeshvadi/mcp-error-classifier with Grok:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "DistilBertForSequenceClassification" | |
| ], | |
| "model_type": "distilbert", | |
| "num_labels": 6, | |
| "id2label": { | |
| "0": "CORRECT", | |
| "1": "TOOL_BYPASS", | |
| "2": "FALSE_SUCCESS", | |
| "3": "HALLUCINATION", | |
| "4": "BROKEN_CHAIN", | |
| "5": "STALE_DATA" | |
| }, | |
| "label2id": { | |
| "CORRECT": 0, | |
| "TOOL_BYPASS": 1, | |
| "FALSE_SUCCESS": 2, | |
| "HALLUCINATION": 3, | |
| "BROKEN_CHAIN": 4, | |
| "STALE_DATA": 5 | |
| }, | |
| "hidden_size": 768, | |
| "max_position_embeddings": 512, | |
| "vocab_size": 30522, | |
| "problem_type": "single_label_classification" | |
| } |