Instructions to use aiface/phobert-base-v2_v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aiface/phobert-base-v2_v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aiface/phobert-base-v2_v3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aiface/phobert-base-v2_v3") model = AutoModelForSequenceClassification.from_pretrained("aiface/phobert-base-v2_v3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model_predict.csv from aiface/phobert-base-v2_v3: direct link, hf CLI and curl.
- Browser
- Download file 807 kB
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https://huggingface.co/aiface/phobert-base-v2_v3/resolve/main/model_predict.csv
- Command line
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hf download hf://aiface/phobert-base-v2_v3/model_predict.csv
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curl -L -o model_predict.csv https://huggingface.co/aiface/phobert-base-v2_v3/resolve/main/model_predict.csv
807 kB
File too large to display, you can check the raw version instead.