初始化项目，由ModelHub XC社区提供模型

Model: NeuralNovel/Panda-7B-v0.1
Source: Original Platform

README.md

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+---
+license: apache-2.0
+base_model: mistralai/Mistral-7B-Instruct-v0.2
+datasets:
+- NeuralNovel/Creative-Logic-v1
+- NeuralNovel/Neural-Story-v1
+library_name: transformers
+inference: false
+---
+![Neural-Story](https://i.ibb.co/TYvZhws/Panda7b.png)
+
+# NeuralNovel/Panda-7B-v0.1
+The **Panda-7B-v0.1** model by NeuralNovel.
+
+This fine-tune has been designed to provide detailed, creative and logical responses in the context of diverse narratives. Optimised for creative writing, roleplay and logical problem solving.
+
+Full-parameter fine-tune (FFT) of Mistral-7B-Instruct-v0.2. Apache-2.0 license, suitable for commercial or non-commercial use.
+
+<a href='https://ko-fi.com/S6S2UH2TC' target='_blank'><img height='38' style='border:0px;height:36px;' src='https://storage.ko-fi.com/cdn/kofi1.png?v=3' border='0' alt='Buy Me a Coffee at ko-fi.com' /></a>
+<a href='https://discord.gg/KFS229xD' target='_blank'><img width='140' height='500' style='border:0px;height:36px;' src='https://i.ibb.co/tqwznYM/Discord-button.png' border='0' alt='Join Our Discord!' /></a>
+
+### Data-set
+The model on finetuned using the Panda-v1 dataset.
+
+### Summary
+
+Fine-tuned with the intention to generate instructive and narrative text, with a specific focus on combining the elements of versatility, character engagement and nuanced writing capability. 
+
+#### 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.
+
+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.*