Instructions to use MutazYoune/Absa_AspectSentiment_hotels with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MutazYoune/Absa_AspectSentiment_hotels with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MutazYoune/Absa_AspectSentiment_hotels")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MutazYoune/Absa_AspectSentiment_hotels") model = AutoModelForSequenceClassification.from_pretrained("MutazYoune/Absa_AspectSentiment_hotels", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from MutazYoune/Absa_AspectSentiment_hotels: direct link, hf CLI and curl.
- Browser
- Download file 436 MB
-
https://huggingface.co/MutazYoune/Absa_AspectSentiment_hotels/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://MutazYoune/Absa_AspectSentiment_hotels/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/MutazYoune/Absa_AspectSentiment_hotels/resolve/main/flax_model.msgpack
436 MB
- Xet hash:
- 1b9eeea397257d4c2f2f8d214f91da3e8f567985a068ab1d4bbb1b07b598fd38
- Size of remote file:
- 436 MB
- SHA256:
- e338ae07e995aa82e0201531ac46483ffc26a963b3f43aa6595c8d93fec216f3
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