Instructions to use hcisbmm/vial_fast_tokenizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hcisbmm/vial_fast_tokenizer with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("hcisbmm/vial_fast_tokenizer", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Upload tokenizer metadata
Browse files- metadata.json +10 -10
metadata.json
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"repo_id": "hcisbmm/vial_insertion",
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"vocab_size": 1024,
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"scale": 10.0,
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"encoded_dims": "
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"encoded_dim_ranges": [
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"total_encoded_dims":
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"delta_dims": null,
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"delta_dim_list": null,
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"use_delta_transform": false,
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"action_horizon": 10,
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"num_training_chunks": 1856,
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"compression_stats": {
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"compression_ratio":
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"mean_token_length":
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"p99_token_length":
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"min_token_length":
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"max_token_length":
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}
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}
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"repo_id": "hcisbmm/vial_insertion",
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"vocab_size": 1024,
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"scale": 10.0,
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"encoded_dims": "0:7,7:14",
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"encoded_dim_ranges": [
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],
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"total_encoded_dims": 14,
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"delta_dims": null,
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"delta_dim_list": null,
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"use_delta_transform": false,
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"action_horizon": 10,
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"num_training_chunks": 1856,
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"compression_stats": {
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"compression_ratio": 5.216289727635158,
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"mean_token_length": 26.839,
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"p99_token_length": 40.0,
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"min_token_length": 7.0,
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"max_token_length": 67.0
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}
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}
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