Instructions to use qandos0/SentimentArEng with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use qandos0/SentimentArEng with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="qandos0/SentimentArEng")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("qandos0/SentimentArEng") model = AutoModelForSequenceClassification.from_pretrained("qandos0/SentimentArEng", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from qandos0/SentimentArEng: direct link, hf CLI and curl.
- Browser
- Download file 1.11 GB
-
https://huggingface.co/qandos0/SentimentArEng/resolve/main/model.safetensors
- Command line
-
hf download hf://qandos0/SentimentArEng/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/qandos0/SentimentArEng/resolve/main/model.safetensors
1.11 GB
- Xet hash:
- b426072e70df73bbc10556f465875320b50fa777f710b4b3fb509adfede32876
- Size of remote file:
- 1.11 GB
- SHA256:
- ae731f52668a8bcbc3d10e22f35155baded5d1960b997f6d509973da5cf4e114
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