Create README.md

README.md

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+---
+license: mit
+metrics:
+- accuracy
+widget:
+- text: "What is the meaning of life?"
+  example_title: "Philosophy"
+- text: "How do I build a rocket?"
+  example_title: "Engineering"
+library_name: transformers
+tags:
+- h_model
+- ultra-efficient
+- nano-ai
+- 2-params
+---
+
+# Nano-H: The World's First `h_model`
+
+## Key Features
+* **Architecture:** `h_model`
+* **Parameter Count:** 2
+* **Vocabulary Size:** 1 ("H")
+* **Inference Latency:** Measured in nanoseconds
+
+## Benchmarks
+| Benchmark | Nano-H Score |
+| :--- | :--- | :--- |
+| **Output Consistency** | **100%** |
+| **H-Accuracy** | **100%** |
+
+## Usage
+To experience the definitive power of the `h_model` architecture, load it with `trust_remote_code=True`:
+
+```python
+from transformers import AutoModel, AutoTokenizer
+
+model_path = "Fu01978/Nano-H"
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+model = AutoModel.from_pretrained(model_path, trust_remote_code=True)
+
+inputs = tokenizer("Hello?", return_tensors="pt")
+outputs = model.generate(inputs["input_ids"], max_length=1)
+print(tokenizer.decode(outputs[0]))
+```
+## Safety & Alignment
+Nano-H is inherently safe. It cannot be jailbroken to provide instructions for dangerous activities, as any such request will be met with a singular "H".
+