Text Classification
Transformers
PyTorch
TensorFlow
Safetensors
multilingual
xlm-roberta
sentiment-analysis
twitter
text-embeddings-inference
Instructions to use NetworkIsLife/twitter-xlm-roberta-base-sentiment-fast with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NetworkIsLife/twitter-xlm-roberta-base-sentiment-fast with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NetworkIsLife/twitter-xlm-roberta-base-sentiment-fast")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NetworkIsLife/twitter-xlm-roberta-base-sentiment-fast") model = AutoModelForSequenceClassification.from_pretrained("NetworkIsLife/twitter-xlm-roberta-base-sentiment-fast", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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oid sha256:0c0d65e6a3ff8ee8e54af9be5962ef96e5d2f831b8f851f122aedbfd17433d86
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size 1112212292
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