---
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
pipeline_tag: text-generation
---

# Nano-H: The World's First `h_model`

**Nano-H** is a revolutionary, ultra-minimalist language model architecture. While the industry trends toward trillion-parameter behemoths, Nano-H proves that with just **2 trainable parameters**, you can achieve 100% precision, 100% recall, and 0% hallucination for the most important character in the alphabet: **H**.

## 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".