Instructions to use paulhindemith/fasttext-jp-embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use paulhindemith/fasttext-jp-embedding with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="paulhindemith/fasttext-jp-embedding", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("paulhindemith/fasttext-jp-embedding", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): 9841823
Update README.nd
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README.md
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@@ -36,7 +36,7 @@ import numpy as np
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text = "海賊王におれはなる"
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pipeline = pipeline("feature-extraction", model="paulhindemith/fasttext-jp-embedding", revision="2022.11.
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pd.DataFrame(np.array(pipeline(text)).T, columns=pipeline.tokenizer.tokenize(text))
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```
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text = "海賊王におれはなる"
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pipeline = pipeline("feature-extraction", model="paulhindemith/fasttext-jp-embedding", revision="2022.11.13", trust_remote_code=True)
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pd.DataFrame(np.array(pipeline(text)).T, columns=pipeline.tokenizer.tokenize(text))
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```
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