Instructions to use mbeukman/xlm-roberta-base-finetuned-amharic-finetuned-ner-swahili with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mbeukman/xlm-roberta-base-finetuned-amharic-finetuned-ner-swahili with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mbeukman/xlm-roberta-base-finetuned-amharic-finetuned-ner-swahili")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mbeukman/xlm-roberta-base-finetuned-amharic-finetuned-ner-swahili") model = AutoModelForTokenClassification.from_pretrained("mbeukman/xlm-roberta-base-finetuned-amharic-finetuned-ner-swahili", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| {"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "model_max_length": 512, "special_tokens_map_file": null, "name_or_path": "Davlan/xlm-roberta-base-finetuned-amharic", "sp_model_kwargs": {}, "tokenizer_class": "XLMRobertaTokenizer"} |