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vit-phi-1half

Text Generation
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PyTorch
mixformer-sequential
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vit-phi-1half
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{
  "_name_or_path": "vit-phi-1.5",
  "activation_function": "gelu_new",
  "architecture": {
    "block_cls": "parallel",
    "mixer": {},
    "mlp": {
      "mlp_cls": "mlp"
    }
  },
  "architectures": [
    "MixFormerVLSequentialForCausalLM"
  ],
  "auto_map": {
    "AutoConfig": "configuration_mixformer_sequential.MixFormerVLSequentialConfig",
    "AutoModelForCausalLM": "modeling_mixformer_sequential.MixFormerVLSequentialForCausalLM"
  },
  "embd_layer": "default",
  "embd_pdrop": 0.0,
  "initializer_range": 0.02,
  "layer_norm_epsilon": 1e-05,
  "model_type": "mixformer-sequential",
  "n_embd": 2048,
  "n_head": 32,
  "n_inner": null,
  "n_layer": 24,
  "n_positions": 2048,
  "phyagi_version": "0.0.4.dev",
  "resid_pdrop": 0.0,
  "rotary_dim": 32,
  "tie_word_embeddings": false,
  "torch_dtype": "float16",
  "transformers_version": "4.32.1",
  "tokenizer_type": "VitPhiTokenizer",
  "visual": {
    "heads": 16,
    "image_size": 448,
    "image_start_id": 50470,
    "layers": 48,
    "mlp_ratio": 4.9231,
    "output_dim": 4096,
    "patch_size": 14,
    "width": 1664
  },
  "vocab_size": 51200
}