Instructions to use iagoalves/sentiment-model-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use iagoalves/sentiment-model-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="iagoalves/sentiment-model-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("iagoalves/sentiment-model-v2") model = AutoModelForSequenceClassification.from_pretrained("iagoalves/sentiment-model-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b8cca8e00c7ffbd60effaa79d88fca0c18fee38174ad336d602ab5cd6b64803e
- Size of remote file:
- 4.6 kB
- SHA256:
- c3a5ef95caf7ba366335bee0700fefa64fbd06ef3a4f9f88b0402ac6f9ac668e
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