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README.md

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 ---
 license: mit
+tags:
+- management
+- text generation
+model-index:
+- name: ManaGPT-1010
+  results: []
+language:
+- en
+pipeline_tag: text-generation
 ---
+
+# ManaGPT-1020
+<img style="float:right; margin:10px; margin-right:30px" src="https://huggingface.co/NeuraXenetica/ManaGPT-1010/resolve/main/ManaGPT_logo_01.png" width="150" height="150"></img>
+**ManaGPT-1020** is an experimental open-source text-generating AI designed to offer insights on the role of emerging technologies in organizational management.
+
+_(Please note that ManaGPT-1020 has superseded by **[ManaGPT-1010](https://huggingface.co/NeuraXenetica/ManaGPT-1010)**: the newer model has been fine-tuned on a dataset roughly 6.45 times the size of that used to fine-tune ManaGPT-1010.)_
+
+## Model description
+
+The model is a fine-tuned version of GPT-2 that has been trained on a custom corpus of scholarly and popular texts from the field of organizational management that relate to ongoing effects of posthumanizing technologies (e.g., relating to advanced artificial intelligence, social robotics, virtual reality, neuroprosthetics, and cyber-physical systems) on the structure of organizations and human beings’ experience of organizational life.
+
+## Intended uses & limitations
+
+This model has been designed for experimental research purposes; it isn’t intended for use in a production setting or in any sensitive or potentially hazardous contexts.
+
+## Training procedure and hyperparameters
+
+The model was trained using a Tesla T4 with 16GB of GPU memory. The following hyperparameters were used during training:
+- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'ExponentialDecay', 'config': {'initial_learning_rate': 0.0005, 'decay_steps': 500, 'decay_rate': 0.95, 'staircase': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
+- training_precision: float32
+
+### Framework versions
+
+- Transformers 4.27.1
+- TensorFlow 2.11.0
+- Datasets 2.10.1
+- Tokenizers 0.13.2

config.json

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+{
+  "_name_or_path": "gpt2",
+  "activation_function": "gelu_new",
+  "architectures": [
+    "GPT2LMHeadModel"
+  ],
+  "attn_pdrop": 0.1,
+  "bos_token_id": 50256,
+  "do_sample": true,
+  "embd_pdrop": 0.1,
+  "eos_token_id": 50256,
+  "initializer_range": 0.02,
+  "layer_norm_epsilon": 1e-05,
+  "max_length": 50,
+  "model_type": "gpt2",
+  "n_ctx": 1024,
+  "n_embd": 768,
+  "n_head": 12,
+  "n_inner": null,
+  "n_layer": 12,
+  "n_positions": 1024,
+  "pad_token_id": 50256,
+  "reorder_and_upcast_attn": false,
+  "resid_pdrop": 0.1,
+  "scale_attn_by_inverse_layer_idx": false,
+  "scale_attn_weights": true,
+  "summary_activation": null,
+  "summary_first_dropout": 0.1,
+  "summary_proj_to_labels": true,
+  "summary_type": "cls_index",
+  "summary_use_proj": true,
+  "task_specific_params": {
+    "text-generation": {
+      "do_sample": true,
+      "max_length": 50
+    }
+  },
+  "transformers_version": "4.27.2",
+  "use_cache": true,
+  "vocab_size": 50257
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 50256,
+  "do_sample": true,
+  "eos_token_id": 50256,
+  "max_length": 50,
+  "pad_token_id": 50256,
+  "transformers_version": "4.27.2"
+}

tf_model.h5

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+oid sha256:5b4c1d25cec73df540aefddb6441e4efb11b1adf598cea7cd0827936cf8d2894
+size 497935440