Text Classification
Transformers
Safetensors
Burmese
xlm-roberta
aspect-based-sentiment-analysis
absa
sentiment-analysis
burmese
myanmar
text-embeddings-inference
Instructions to use Fixaro/myanmar-absa-sentiment-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Fixaro/myanmar-absa-sentiment-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Fixaro/myanmar-absa-sentiment-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Fixaro/myanmar-absa-sentiment-classification") model = AutoModelForSequenceClassification.from_pretrained("Fixaro/myanmar-absa-sentiment-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 469 Bytes
9c54276 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | {
"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>",
"max_length": 128,
"model_max_length": 512,
"pad_token": "<pad>",
"sep_token": "</s>",
"stride": 0,
"tokenizer_class": "XLMRobertaTokenizer",
"truncation_side": "right",
"truncation_strategy": "longest_first",
"unk_token": "<unk>"
}
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