Text Classification
Transformers
PyTorch
Safetensors
Polish
roberta
feature-extraction
text-embeddings-inference
Instructions to use hplisiecki/polemo_intensity with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hplisiecki/polemo_intensity with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hplisiecki/polemo_intensity")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hplisiecki/polemo_intensity") model = AutoModel.from_pretrained("hplisiecki/polemo_intensity", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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from polemo_intensity.model_script import Model # importing the custom model class
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from transformers import AutoTokenizer
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model_directory = "polemo_intensity" # path to the
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model = Model.from_pretrained(model_directory)
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tokenizer = AutoTokenizer.from_pretrained(model_directory)
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inputs = tokenizer("This is a test input.", return_tensors="pt")
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from polemo_intensity.model_script import Model # importing the custom model class
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from transformers import AutoTokenizer
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model_directory = "C:placeholder/polemo_intensity" # Your full path to the model's directory
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model = Model.from_pretrained(model_directory)
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tokenizer = AutoTokenizer.from_pretrained(model_directory)
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inputs = tokenizer("This is a test input.", return_tensors="pt")
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