Update README.md

README.md

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 This model was converted to GGUF format from [`Replete-AI/L3.1-Pneuma-8B`](https://huggingface.co/Replete-AI/L3.1-Pneuma-8B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
 Refer to the [original model card](https://huggingface.co/Replete-AI/L3.1-Pneuma-8B) for more details on the model.
 
+---
+Model details:
+-
+This model is a fine-tuned version of meta-llama/Llama-3.1-8B-Instruct on the Sandevistan dataset. It achieves the following results on the evaluation set:
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+Loss: 2.4357
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+This model is designed to challenge common paradigms in training Large Language Models, giving them a focus on user experience over profitability. These are highly experimental, and need preference training in order to increase their effectiveness. It seems to have retained a large amount of the biases that we were trying to eliminate from the corporate instruct models.
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+Intended uses & limitations
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+Chatting, conversation, and assistance in small downstream tasks.
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+Large Language Models work incredibly differently from humans, so while we are capable of training and rewarding them to act just like us in many ways, you should treat it as a simulation and use the Socratic method when engaging with them. You, as an end-user should always remain in control of your own thoughts and decisions, and use AI as a way to improve yourself rather than becoming dependent on it.
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+Training procedure
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+Training hyperparameters
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+The following hyperparameters were used during training:
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+    learning_rate: 7.8e-06
+    train_batch_size: 8
+    eval_batch_size: 8
+    seed: 42
+    gradient_accumulation_steps: 16
+    total_train_batch_size: 128
+    optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+    lr_scheduler_type: cosine
+    num_epochs: 2
+
+---
 ## Use with llama.cpp
 Install llama.cpp through brew (works on Mac and Linux)