Text Classification
Transformers
Safetensors
multilingual
snt_classifier
feature-extraction
news
topic-classification
multi-label
xlm-roberta
custom_code
Instructions to use sweenk/snt-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sweenk/snt-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sweenk/snt-classifier", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("sweenk/snt-classifier", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 342 Bytes
39ddcbc | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | {
"add_prefix_space": true,
"backend": "tokenizers",
"bos_token": "<s>",
"cls_token": "<s>",
"eos_token": "</s>",
"is_local": true,
"local_files_only": false,
"mask_token": "<mask>",
"model_max_length": 512,
"pad_token": "<pad>",
"sep_token": "</s>",
"tokenizer_class": "XLMRobertaTokenizer",
"unk_token": "<unk>"
}
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