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README.md

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+---
+license: apache-2.0
+base_model: mistralai/Mistral-7B-Instruct-v0.2
+datasets:
+- NeuralNovel/Neural-Story-v1
+library_name: transformers
+inference: false
+language:
+- en
+---
+
+![Neural-Story](https://i.ibb.co/JFRYk6g/OIG-27.jpg)
+# NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story
+[GGUF FILES HERE](https://huggingface.co/Kquant03/Mistral-7B-Instruct-v0.2-Neural-Story-GGUF)
+
+
+The **Mistral-7B-Instruct-v0.2-Neural-Story** model, developed by NeuralNovel and funded by Techmind, is a language model finetuned from Mistral-7B-Instruct-v0.2.
+
+Designed to generate instructive and narrative text, with a specific focus on storytelling.
+This fine-tune has been tailored to provide detailed and creative responses in the context of narrative and optimised for short story telling.
+
+Based on mistralAI, with apache-2.0 license, suitable for commercial or non-commercial use.
+
+### Data-set
+The model was finetuned using the Neural-Story-v1 dataset.
+
+### Benchmark
+| Metric                | Value                     |
+|-----------------------|---------------------------|
+| Avg.                  | **64.96**   |
+| ARC          | 64.08          |
+| HellaSwag    | **66.89**   |
+| MMLU         | 60.67         |
+| TruthfulQA    | 66.89   |
+| Winogrande    | **75.85**   |
+| GSM8K         | 38.29        |
+
+Evaluated on **HuggingFaceH4/open_llm_leaderboard**
+
+### Summary
+
+Fine-tuned with the intention of generating creative and narrative text, making it more suitable for creative writing prompts and storytelling.
+
+#### Out-of-Scope Use
+
+The model may not perform well in scenarios unrelated to instructive and narrative text generation. Misuse or applications outside its designed scope may result in suboptimal outcomes.
+
+### Bias, Risks, and Limitations
+
+The model may exhibit biases or limitations inherent in the training data. It is essential to consider these factors when deploying the model to avoid unintended consequences.
+
+While the Neural-Story-v0.1 dataset serves as an excellent starting point for testing language models, users are advised to exercise caution, as there might be some inherent genre or writing bias.
+
+### Hardware and Training
+
+
+```
+
+  n_epochs = 3,
+  n_checkpoints = 3,
+  batch_size = 12,
+  learning_rate = 1e-5,
+
+
+
+```
+
+*Sincere appreciation to Techmind for their generous sponsorship.*

config.json

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+{
+  "_name_or_path": "/mnt/models/Mistral-7B-Instruct-v0.2-Neural-Story",
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 32768,
+  "model_type": "mistral",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "quantization_config": {
+    "bits": 4,
+    "group_size": 128,
+    "modules_to_not_convert": null,
+    "quant_method": "awq",
+    "version": "gemm",
+    "zero_point": true
+  },
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 1000000.0,
+  "sliding_window": 4096,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.37.2",
+  "use_cache": true,
+  "vocab_size": 32000
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "do_sample": true,
+  "eos_token_id": 2,
+  "transformers_version": "4.37.2"
+}

model.safetensors

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