Instructions to use CodeIsAbstract/HybridTimeScaleModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CodeIsAbstract/HybridTimeScaleModel with Transformers:
# Load model directly from transformers import HybridFourierLM model = HybridFourierLM.from_pretrained("CodeIsAbstract/HybridTimeScaleModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 400
Browse files- config.json +33 -0
- generation_config.json +9 -0
- model.safetensors +3 -0
- training_args.bin +3 -0
config.json
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{
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"architectures": [
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"HybridFourierLM"
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],
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"bos_token_id": 1,
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"dropout": 0.05,
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"dtype": "float32",
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"eos_token_id": 2,
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"latent_dim": 768,
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"layer_types": [
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"linear",
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"linear",
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"linear",
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"softmax",
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"linear",
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"linear",
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"linear",
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"softmax",
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"linear",
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"linear",
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"linear",
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"softmax"
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],
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"model_type": "hybrid_fourier_lm",
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"num_layers": 12,
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"num_modes": 64,
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"pad_token_id": 2,
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"tie_word_embeddings": true,
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"time_scale": 128.0,
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"transformers_version": "5.13.1",
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"use_cache": false,
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"vocab_size": 32768
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}
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"output_attentions": false,
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"output_hidden_states": false,
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"pad_token_id": 2,
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"transformers_version": "5.13.1"
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:4570a7676418e7c1dbde619776b27e38071294b6d1f599604c28b8750b0802b3
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size 469337272
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:a3b71add29216572affacbd140d488514e006cd0cdd1bd77cb7bc84501d9c04c
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size 5201
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