Instructions to use DSI/personal_sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DSI/personal_sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DSI/personal_sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DSI/personal_sentiment") model = AutoModelForSequenceClassification.from_pretrained("DSI/personal_sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| {"py/object": "pet.wrapper.WrapperConfig", "model_type": "bert", "model_name_or_path": "arabic_multilabel_2ipet/g1/p1-i1", "wrapper_type": "sequence_classifier", "task_name": "arabic_multilabel", "max_seq_length": 256, "label_list": ["no_ref", "neutral", "positive", "negative"], "pattern_id": 0, "verbalizer_file": null, "cache_dir": ""} |