Text Classification
Transformers
Safetensors
English
distilbert
intent detection
distilBert
E-commerce
text-embeddings-inference
Instructions to use monish-sd-7/E-Commerce-Customer-Intent-Detection-Model-Finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use monish-sd-7/E-Commerce-Customer-Intent-Detection-Model-Finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="monish-sd-7/E-Commerce-Customer-Intent-Detection-Model-Finetuned")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("monish-sd-7/E-Commerce-Customer-Intent-Detection-Model-Finetuned") model = AutoModelForSequenceClassification.from_pretrained("monish-sd-7/E-Commerce-Customer-Intent-Detection-Model-Finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from monish-sd-7/E-Commerce-Customer-Intent-Detection-Model-Finetuned: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
-
https://huggingface.co/monish-sd-7/E-Commerce-Customer-Intent-Detection-Model-Finetuned/resolve/918505f4b724162dbc9c0519f037bdae7997d5db/tokenizer.json
- Command line
-
hf download hf://monish-sd-7/E-Commerce-Customer-Intent-Detection-Model-Finetuned@918505f4b724162dbc9c0519f037bdae7997d5db/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/monish-sd-7/E-Commerce-Customer-Intent-Detection-Model-Finetuned/resolve/918505f4b724162dbc9c0519f037bdae7997d5db/tokenizer.json
712 kB
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