Instructions to use datasetsANDmodels/message-extraction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use datasetsANDmodels/message-extraction with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("datasetsANDmodels/message-extraction") model = AutoModelForSeq2SeqLM.from_pretrained("datasetsANDmodels/message-extraction", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download usage.py from datasetsANDmodels/message-extraction: direct link, hf CLI and curl.
- Browser
- Download file 309 Bytes
-
https://huggingface.co/datasetsANDmodels/message-extraction/resolve/main/usage.py
- Command line
-
hf download hf://datasetsANDmodels/message-extraction/usage.py
-
curl -L -o usage.py https://huggingface.co/datasetsANDmodels/message-extraction/resolve/main/usage.py
309 Bytes
| from transformers import pipeline | |
| extractor = pipeline("text2text-generation", model=".") | |
| import pandas as pd | |
| df = pd.read_csv("message.csv") | |
| texts=df["message"] | |
| for intent in texts: | |
| label=extractor(intent)[0]["generated_text"] | |
| if label=="": | |
| label="No message detected" | |
| print (label ) | |