Instructions to use datasetsANDmodels/request-extraction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use datasetsANDmodels/request-extraction with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("datasetsANDmodels/request-extraction") model = AutoModelForSeq2SeqLM.from_pretrained("datasetsANDmodels/request-extraction", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download usage.py from datasetsANDmodels/request-extraction: direct link, hf CLI and curl.
- Browser
- Download file 361 Bytes
-
https://huggingface.co/datasetsANDmodels/request-extraction/resolve/main/usage.py
- Command line
-
hf download hf://datasetsANDmodels/request-extraction/usage.py
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curl -L -o usage.py https://huggingface.co/datasetsANDmodels/request-extraction/resolve/main/usage.py
361 Bytes
| from transformers import pipeline | |
| extractor = pipeline("text2text-generation", model="request-extraction") | |
| intent ="I really need my broken window to be replaced, can John do it by today" | |
| intent = " Can you come and have a look at our boiler" | |
| label=extractor(intent)[0]["generated_text"] | |
| if label=="": | |
| label="No request detected" | |
| print (label ) |