Instructions to use shuaifan/SentiWSP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shuaifan/SentiWSP with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="shuaifan/SentiWSP")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("shuaifan/SentiWSP") model = AutoModelForSequenceClassification.from_pretrained("shuaifan/SentiWSP") - Notebooks
- Google Colab
- Kaggle
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## Fine-tunning
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You can also load our model in huggingface ([https://huggingface.co/shuaifan/SentiWSP](https://huggingface.co/shuaifan/SentiWSP)):
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```python
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import torch
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model =
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tokenizer = ElectraTokenizer.from_pretrained("shuaifan/SentiWSP")
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```
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## Fine-tunning
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You can also load our model in huggingface ([https://huggingface.co/shuaifan/SentiWSP](https://huggingface.co/shuaifan/SentiWSP)):
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```python
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from transformers import AutoTokenizer, AutoModelForSequenceClassification
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import torch
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tokenizer = AutoTokenizer.from_pretrained("shuaifan/SentiWSP")
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model = AutoModelForSequenceClassification.from_pretrained("shuaifan/SentiWSP")
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```
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