Instructions to use HiAmNear/mbert-base-uncased-ViFE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HiAmNear/mbert-base-uncased-ViFE with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HiAmNear/mbert-base-uncased-ViFE")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HiAmNear/mbert-base-uncased-ViFE") model = AutoModelForSequenceClassification.from_pretrained("HiAmNear/mbert-base-uncased-ViFE", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from HiAmNear/mbert-base-uncased-ViFE: direct link, hf CLI and curl.
- Browser
- Download file 2.56 MB
-
https://huggingface.co/HiAmNear/mbert-base-uncased-ViFE/resolve/main/tokenizer.json
- Command line
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hf download hf://HiAmNear/mbert-base-uncased-ViFE/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/HiAmNear/mbert-base-uncased-ViFE/resolve/main/tokenizer.json
2.56 MB
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