Text Classification
Transformers
Safetensors
gemma3_text
gemma3
intent-classification
multilingual
text-embeddings-inference
Instructions to use blue-machines/Multilingual_Intent_Classifier_checkpoint_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use blue-machines/Multilingual_Intent_Classifier_checkpoint_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="blue-machines/Multilingual_Intent_Classifier_checkpoint_v1")# Load model directly from transformers import AutoTokenizer, Gemma3Intent8LStudent tokenizer = AutoTokenizer.from_pretrained("blue-machines/Multilingual_Intent_Classifier_checkpoint_v1") model = Gemma3Intent8LStudent.from_pretrained("blue-machines/Multilingual_Intent_Classifier_checkpoint_v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download label_map.json from blue-machines/Multilingual_Intent_Classifier_checkpoint_v1: direct link, hf CLI and curl.
- Browser
- Download file 727 Bytes
-
https://huggingface.co/blue-machines/Multilingual_Intent_Classifier_checkpoint_v1/resolve/main/label_map.json
- Command line
-
hf download hf://blue-machines/Multilingual_Intent_Classifier_checkpoint_v1/label_map.json
-
curl -L -o label_map.json https://huggingface.co/blue-machines/Multilingual_Intent_Classifier_checkpoint_v1/resolve/main/label_map.json
727 Bytes
| { | |
| "head4_intent": { | |
| "label2id": { | |
| "provide_info": 0, | |
| "affirm": 1, | |
| "deny": 2, | |
| "correction": 3, | |
| "question": 4, | |
| "clarify_request": 5, | |
| "unclear": 6 | |
| }, | |
| "id2label": { | |
| "0": "provide_info", | |
| "1": "affirm", | |
| "2": "deny", | |
| "3": "correction", | |
| "4": "question", | |
| "5": "clarify_request", | |
| "6": "unclear" | |
| } | |
| }, | |
| "languages": [ | |
| "hindi", | |
| "tamil", | |
| "telugu", | |
| "kannada", | |
| "marathi", | |
| "malayalam", | |
| "bengali", | |
| "gujarati", | |
| "odia", | |
| "english" | |
| ], | |
| "dataset": "blue-machines/multilingual_indic_intent_classification_data", | |
| "kept_teacher_layers": [ | |
| 0, | |
| 2, | |
| 5, | |
| 7, | |
| 10, | |
| 12, | |
| 15, | |
| 17 | |
| ] | |
| } |