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PhillnetLargeQuantized

Text Generation
Transformers
PyTorch
English
gpt2
feature-extraction
text-generation-inference
Inference Endpoints
Model card Files Community
PhillnetLargeQuantized
File size: 1,755 Bytes 
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{
  "activation_function": "gelu_new",
  "architectures": ["GPT2LMHeadModel"],
  "attn_pdrop": 0.1,
  "bos_token_id": 50256,
  "embd_pdrop": 0.1,
  "eos_token_id": 50256,
  "initializer_range": 0.02,
  "layer_norm_epsilon": 1e-05,
  "model_type": "gpt2",
  "n_ctx": 2048,
  "n_embd": 2048,
  "n_head": 16,
  "n_layer": 24,
  "n_positions": 2048,
  "predict_special_tokens": true,
  "resid_pdrop": 0.1,
  "transformers_version": "4.34.0",
  "vocab_size": 50257,  // Adjusted to include special tokens
  "task_specific_params": {
    "text-generation": {
      "do_sample": true,
      "max_length": 2048
    }
  },
  "language": ["en"],
  "tags": ["text-generation-inference"],
  "metrics": ["accuracy"],
  "pipeline_tag": "text-generation",
  "library_name": "transformers",
  "license": "apache-2.0",
  "custom_params": {
    "adaptation_rate": 0.05,
    "ecosystem_dynamics": {
      "environmental_volatility": 0.1,
      "resource_pool": 1
    },
    "hidden_dim": 2048,
    "initial_neuron_count": 5000,
    "innovative_growth_net": {
      "adaptation_rate": 0.05,
      "initial_capacity": 250000,
      "input_size": 2048
    },
    "max_complexity": 50000,
    "max_neurons": 250000,
    "max_sequence_length": 2048,
    "min_epochs_before_growth": 5,
    "model_filename": "pytorch_model.bin",
    "num_embeddings": 100000,
    "pruning_improvement_threshold": 0.005,
    "some_adaptation_rate": 0.05,
    "stability_threshold": 0.02,
    "start_token_index": 2
  },
  "max_input_length": 2048,
  "max_total_tokens": 2051,
  "max_concurrent_requests": 128,
  "max_best_of": 2,
  "max_stop_sequences": 4,
  "max_top_n_tokens": 5,
  "waiting_served_ratio": 1.2,
  "max_batch_prefill_tokens": 2048,
  "max_waiting_tokens": 20,
  "sharded": false
}