Update README.md

README.md

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 ---
-title: Prometh-MOEM-V.01 Model Demo
+title: Prometh-MOEM-V.01 Model Showcase
 emoji: 👁
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 colorTo: pink
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 - en
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+# Prometh-MOEM-V.01 Model Card 👁
+
+**Prometh-MOEM-V.01** is a pioneering Mixture of Experts (MoE) model, blending the capabilities of multiple foundational models to enhance performance across a variety of tasks. This model leverages the collective strengths of its components, achieving unparalleled accuracy, speed, and versatility.
+
+## 🚀 Model Sources and Components
+
+This MoE model amalgamates specialized models including:
+
+- [Wtzwho/Prometh-merge-test2](https://huggingface.co/Wtzwho/Prometh-merge-test2)
+- [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2)
+- [Wtzwho/Prometh-merge-test3](https://huggingface.co/Wtzwho/Prometh-merge-test3)
+- [meta-math/MetaMath-Mistral-7B](https://huggingface.co/meta-math/MetaMath-Mistral-7B)
+
+## 🌟 Key Features
+
+- **Enhanced Performance**: Tailored for peak accuracy and efficiency.
+- **Versatility**: Exceptionally adaptable across a wide range of NLP tasks.
+- **State-of-the-Art Integration**: Incorporates the latest in AI research for effective model integration.
+
+## 📈 Application Areas
+
+Prometh-MOEM-V.01 excels in:
+
+- Text generation
+- Sentiment analysis
+- Language translation
+- Question answering
+
+## 💻 Usage Instructions
+
+To utilize Prometh-MOEM-V.01 in your projects:
+
+```python
+pip install -qU transformers bitsandbytes accelerate
+
+from transformers import AutoTokenizer, pipeline
+import torch
+
+model = "Wtzwho/Prometh-MOEM-V.01"
+tokenizer = AutoTokenizer.from_pretrained(model)
+
+# Setup pipeline
+pipeline = pipeline(
+    "text-generation",
+    model=model,
+    model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
+)
+
+# Example query
+messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}]
+prompt = 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"])
+```