Update README.md

README.md

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----
-license: mit
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+# Tiny-LLM
+
+A Tiny LLM model with just 10 Million parameters, this is probably one of the small LLM arounds, and it is functional.
+
+## Pretraining
+
+Tiny-LLM was trained on 32B tokens of the Fineweb dataset, with a context length of 1024 tokens.
+
+## Getting Started
+
+To start using these models, you can simply load them via the Hugging Face `transformers` library:
+
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+
+MODEL_NAME = "arnir0/Tiny-LLM"
+
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+model = AutoModelForCausalLM.from_pretrained(MODEL_NAME)
+
+def generate_text(prompt, model, tokenizer, max_length=512, temperature=1, top_k=50, top_p=0.95):
+    inputs = tokenizer.encode(prompt, return_tensors="pt")
+
+    outputs = model.generate(
+        inputs,
+        max_length=max_length,
+        temperature=temperature,
+        top_k=top_k,
+        top_p=top_p,
+        do_sample=True
+    )
+
+
+    generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return generated_text
+
+def main():
+    # Define your prompt
+    prompt = "According to all known laws of aviation, there is no way a bee should be able to fly."
+
+    generated_text = generate_text(prompt, model, tokenizer)
+
+    print(generated_text)
+
+if __name__ == "__main__":
+    main()
+```