Divyasreepat
commited on
Commit
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Upload folder using huggingface_hub
Browse files- README.md +20 -0
- assets/tokenizer/vocabulary.spm +0 -0
- config.json +22 -0
- metadata.json +6 -0
- model.weights.h5 +3 -0
- tokenizer.json +16 -0
README.md
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---
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library_name: keras-hub
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---
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This is a [`Mistral` model](https://keras.io/api/keras_hub/models/mistral) uploaded using the KerasHub library and can be used with JAX, TensorFlow, and PyTorch backends.
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Model config:
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* **name:** mistral_backbone_1
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* **trainable:** True
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* **vocabulary_size:** 32000
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* **num_layers:** 32
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* **num_query_heads:** 32
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* **hidden_dim:** 4096
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* **intermediate_dim:** 14336
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* **rope_max_wavelength:** 10000.0
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* **rope_scaling_factor:** 1.0
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* **num_key_value_heads:** 8
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* **sliding_window:** 4096
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* **layer_norm_epsilon:** 1e-05
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* **dropout:** 0
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This model card has been generated automatically and should be completed by the model author. See [Model Cards documentation](https://huggingface.co/docs/hub/model-cards) for more information.
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assets/tokenizer/vocabulary.spm
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Binary file (493 kB). View file
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config.json
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{
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"module": "keras_nlp.models.mistral.mistral_backbone",
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"class_name": "MistralBackbone",
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"config": {
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"name": "mistral_backbone_1",
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"trainable": true,
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"vocabulary_size": 32000,
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"num_layers": 32,
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"num_query_heads": 32,
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"hidden_dim": 4096,
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"intermediate_dim": 14336,
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"rope_max_wavelength": 10000.0,
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"rope_scaling_factor": 1.0,
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"num_key_value_heads": 8,
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"sliding_window": 4096,
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"layer_norm_epsilon": 1e-05,
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"dropout": 0
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},
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"registered_name": "keras_nlp>MistralBackbone",
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"assets": [],
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"weights": "model.weights.h5"
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}
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metadata.json
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{
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"keras_version": "3.0.5",
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"keras_nlp_version": "0.8.0",
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"parameter_count": 7241732096,
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"date_saved": "2024-02-23@01:22:25"
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}
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model.weights.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:91483f6833da39601c13bcdbc65439b385117959f32a24bda15774670dcff768
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size 14484497176
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tokenizer.json
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{
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"module": "keras_nlp.models.mistral.mistral_tokenizer",
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"class_name": "MistralTokenizer",
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"config": {
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"name": "mistral_tokenizer",
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"trainable": true,
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"dtype": "int32",
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"proto": null,
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"sequence_length": null
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},
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"registered_name": "keras_nlp>MistralTokenizer",
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"assets": [
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"assets/tokenizer/vocabulary.spm"
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],
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"weights": null
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}
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