Create README.md

README.md

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+---
+license: apache-2.0
+tags:
+- moe
+- mergekit
+---
+
+# NeuralMix-2x7b
+
+This model is a Mixure of Experts (MoE) made with [mergekit](https://github.com/cg123/mergekit) (mixtral branch). It uses the following base models:
+ * [OpenPipe/mistral-ft-optimized-1218](https://huggingface.co/OpenPipe/mistral-ft-optimized-1218)
+ * [mlabonne/NeuralHermes-2.5-Mistral-7B](https://huggingface.co/mlabonne/NeuralHermes-2.5-Mistral-7B)
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers bitsandbytes accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "mlabonne/NeuralMix-2x7b"
+
+tokenizer = AutoTokenizer.from_pretrained(model)
+pipeline = transformers.pipeline(
+    "text-generation",
+    model=model,
+    model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
+)
+
+messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}]
+prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
+print(outputs[0]["generated_text"])
+```
+
+Output:
+```
+A Mixture of Experts (ME) is a neural network architecture that allows for adaptive specialization of its hidden layers. It consists of an input layer, a mixture of expert layers with a set of hidden layers, and an output layer. The expert layers have different specializations and each one is responsible for predicting the output for a particular subset of the input data. The mixture of experts uses a gating network to dynamically select the expert layer that best fits the current input data. This adaptive approach can improve the performance and generalization capabilities of the neural network. 
+
+The Mixture of Experts model is particularly useful in situations where the data is complex, heterogeneous, or has varying structures. By enabling each expert to specialize in a particular type of input, the Mixture of Experts can learn to effectively handle diverse input data and provide more accurate predictions. 
+
+Overall, the Mixture of Experts can be seen as a type of neural network that combines the strengths of multiple models to create a more powerful and flexible predictive tool. 
+```