diff --git a/Dockerfile b/Dockerfile
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+FROM nvidia/cuda:11.8.0-cudnn8-devel-ubuntu22.04
+
+RUN apt-get update && apt-get install -y \
+    python3 \
+    python3-pip
+
+RUN pip3 install torch transformers
+
+WORKDIR /app
+
+COPY run_models.py /app/
+
+CMD ["python3", "run_models.py"]
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diff --git a/img/nosana_logo.png b/img/nosana_logo.png
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diff --git a/run_models.py b/run_models.py
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+++ b/run_models.py
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+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+models = [
+    "mistralai/Mistral-7B-Instruct-v0.2",  # Mistral
+    "Qwen/Qwen1.5-72B-Chat",  # Qwen 1.5
+    "meta-llama/Llama-2-7b",  # Llama 2
+    "databricks/dbrx-instruct",  # DBRX
+    "01-ai/Yi-34B-200K",  # Yi
+    "xai-org/grok-1",  # Grok
+]
+
+prompts = [
+    "What is the capital of France?",
+    "Explain the concept of artificial intelligence in simple terms.",
+    "Write a short story about a robot who dreams of becoming human.",
+    "What are the benefits of regular exercise?",
+    "How can we reduce our carbon footprint to combat climate change?",
+]
+
+for model_name in models:
+    print(f"Running model: {model_name}")
+    print("---")
+
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+    model = AutoModelForCausalLM.from_pretrained(model_name)
+
+    for prompt in prompts:
+        input_ids = tokenizer.encode(prompt, return_tensors="pt")
+        output = model.generate(input_ids, max_length=100)
+        generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
+
+        print(f"Prompt: {prompt}")
+        print(f"Generated text: {generated_text}")
+        print("---")
+
+    print("\n")
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