Instructions to use gunkaynar/bert-base-multilingual-uncased-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gunkaynar/bert-base-multilingual-uncased-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gunkaynar/bert-base-multilingual-uncased-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gunkaynar/bert-base-multilingual-uncased-sentiment") model = AutoModelForSequenceClassification.from_pretrained("gunkaynar/bert-base-multilingual-uncased-sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:92387391416e3cd1a221f681d48ef76f3307158264bc8057b6c9e8e50ab54460
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size 669464588
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