|
|
--- |
|
|
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". |
