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 tokenizer.json from blue-machines/Multilingual_Intent_Classifier_checkpoint_v1: direct link, hf CLI and curl.
- Browser
- Download file 33.4 MB
-
https://huggingface.co/blue-machines/Multilingual_Intent_Classifier_checkpoint_v1/resolve/main/tokenizer.json
- Command line
-
hf download hf://blue-machines/Multilingual_Intent_Classifier_checkpoint_v1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/blue-machines/Multilingual_Intent_Classifier_checkpoint_v1/resolve/main/tokenizer.json
33.4 MB
- Xet hash:
- 0479ca8bffd44a622f4606a732bc6dc6f47b02c3a26eb85860d4d2b9926a597b
- Size of remote file:
- 33.4 MB
- SHA256:
- 5926c550e487d3b4a7012cb60dc69f510a7759e1b97244833ddc95722fe05709
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