Text Classification
Transformers
PyTorch
JAX
English
bert
industry tags
buisiness description
multi-label
classification
inference
Instructions to use sampathkethineedi/industry-classification-api with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sampathkethineedi/industry-classification-api with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sampathkethineedi/industry-classification-api")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sampathkethineedi/industry-classification-api") model = AutoModelForSequenceClassification.from_pretrained("sampathkethineedi/industry-classification-api", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from sampathkethineedi/industry-classification-api: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/sampathkethineedi/industry-classification-api/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://sampathkethineedi/industry-classification-api@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/sampathkethineedi/industry-classification-api/resolve/refs%2Fpr%2F1/pytorch_model.bin
438 MB
- Xet hash:
- d589aaeb68db751ced80d534e5340aea08d3607ea577117a493608e4d900e31d
- Size of remote file:
- 438 MB
- SHA256:
- 06e9c81bf52ff2c50240684d98bb2990e90a4c66b9f29d410718d678db1407ed
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