Update README.md

README.md

@@ -10,57 +10,3 @@ language:
 - 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"])