Instructions to use vocabtrimmer/xlm-v-base-tweet-sentiment-it-trimmed-it-5000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vocabtrimmer/xlm-v-base-tweet-sentiment-it-trimmed-it-5000 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="vocabtrimmer/xlm-v-base-tweet-sentiment-it-trimmed-it-5000")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("vocabtrimmer/xlm-v-base-tweet-sentiment-it-trimmed-it-5000") model = AutoModelForSequenceClassification.from_pretrained("vocabtrimmer/xlm-v-base-tweet-sentiment-it-trimmed-it-5000") - Notebooks
- Google Colab
- Kaggle
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