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 model.safetensors from monish-sd-7/E-Commerce-Customer-Intent-Detection-Model-Finetuned: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/monish-sd-7/E-Commerce-Customer-Intent-Detection-Model-Finetuned/resolve/main/model.safetensors
- Command line
-
hf download hf://monish-sd-7/E-Commerce-Customer-Intent-Detection-Model-Finetuned/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/monish-sd-7/E-Commerce-Customer-Intent-Detection-Model-Finetuned/resolve/main/model.safetensors
268 MB
- Xet hash:
- 83db5b003d1c6ca2379ad5c118a06e746224649ddec5b7b12d8bf53cb6a8750d
- Size of remote file:
- 268 MB
- SHA256:
- 4879a91786da242730c39d4c0e20cfb9456b612d3cccfdc33bbe9f1cf567dc26
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