Add app.py, config.json, README.md, and requirements.txt

README.md

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+# CSM-1B Maya Model
+
+This is the CSM-1B Maya-like conversational model.
+
+## Description
+
+A large language model trained for conversational AI, designed to simulate Maya.
+
+## Usage
+
+You can interact with this model via the Hugging Face Spaces app or load it using custom scripts.
+
+## License
+
+Specify your license here (e.g., MIT, Apache 2.0).

app.py

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+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+import gradio as gr
+
+# Load tokenizer and model with trust_remote_code=True
+tokenizer = AutoTokenizer.from_pretrained("BWComedian/CSM-1B", trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained("BWComedian/CSM-1B", trust_remote_code=True)
+
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model.to(device)
+
+def generate_response(prompt):
+    inputs = tokenizer(prompt, return_tensors="pt").to(device)
+    outputs = model.generate(
+        **inputs,
+        max_length=200,
+        do_sample=True,
+        top_p=0.95,
+        top_k=50,
+        pad_token_id=tokenizer.eos_token_id
+    )
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return response
+
+demo = gr.Interface(
+    fn=generate_response,
+    inputs=gr.Textbox(lines=5, placeholder="Talk to Maya..."),
+    outputs=gr.Textbox(label="Maya says", lines=10),
+    title="CSM-1B Maya Chatbot",
+    description="Chat with your Maya-like model."
+)
+
+if __name__ == "__main__":
+    demo.launch()

config.json

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+{
+  "model_type": "gpt2",
+  "architectures": ["GPT2LMHeadModel"],
+  "hidden_size": 768,
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "vocab_size": 50257
+}

requirements.txt

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+transformers
+torch
+gradio