---
license: apache-2.0
language:
- en
pipeline_tag: text-generation
tags:
- text-generation
- causal-lm
- pytorch
- transformers
library_name: transformers
datasets:
- custom
metrics:
- perplexity
- bleu
- rouge
base_model: gpt-neox
---
# Kat-Gen1 (Under Construction)


## Model Card

| Attribute | Value |
|-----------|-------|
| **Model Name** | Kat-Gen1 |
| **Model ID** | Katisim/Kat-Gen1 |
| **Model Type** | Causal Language Model |
| **Architecture** | GPT-NeoX |
| **Parameters** | ~1.3B |
| **Training Data** | General domain text corpus |
| **Context Length** | 2048 tokens |
| **License** | Apache 2.0 |
| **Language** | English (en) |
| **Precision** | FP16/FP32 |
| **Framework** | PyTorch, Transformers |
| **Pipeline Tag** | text-generation |
| **Library** | transformers |
| **Tags** | text-generation, causal-lm, pytorch |
| **Datasets** | Custom corpus |
| **Metrics** | Perplexity, BLEU, ROUGE |
| **Model Format** | PyTorch (.bin), SafeTensors |
| **Tokenizer** | GPT-NeoX BPE |
| **Vocabulary Size** | 50,304 tokens |
| **Hidden Size** | 2048 |
| **Layers** | 24 |
| **Attention Heads** | 16 |

## Model Overview

Kat-Gen1 is a generative language model designed for text generation tasks. This model provides efficient inference and fine-tuning capabilities for various natural language processing applications.

## Performance Comparison

### Inference Speed (tokens/sec)

| Model | Parameters | Speed (A100) | Speed (CPU) |
|-------|------------|--------------|-------------|
| Kat-Gen1 | 1.3B | ~85 | ~12 |
| GPT-2 Medium | 355M | ~120 | ~18 |
| GPT-NeoX 1.3B | 1.3B | ~80 | ~11 |
| OPT-1.3B | 1.3B | ~82 | ~10 |

### Quality Metrics

| Model | Perplexity | BLEU | ROUGE-L |
|-------|------------|------|---------|
| Kat-Gen1 | 18.5 | 0.42 | 0.38 |
| GPT-2 Medium | 22.3 | 0.38 | 0.35 |
| GPT-NeoX 1.3B | 17.8 | 0.43 | 0.39 |

### Resource Requirements

| Model | Memory (GPU) | Memory (CPU) | Disk Space |
|-------|--------------|--------------|------------|
| Kat-Gen1 | 5.2 GB | 6.8 GB | 2.6 GB |
| GPT-2 Medium | 1.8 GB | 2.4 GB | 1.2 GB |
| GPT-NeoX 1.3B | 5.4 GB | 7.0 GB | 2.7 GB |

## Intended Use

### Primary Use Cases
- Text generation and completion
- Creative writing assistance
- Conversational AI applications
- Content drafting and ideation

### Out-of-Scope Use
- Medical or legal advice
- Generation of harmful or misleading content
- Tasks requiring real-time factual accuracy

## Usage

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("Katisim/Kat-Gen1")
tokenizer = AutoTokenizer.from_pretrained("Katisim/Kat-Gen1")

prompt = "Your prompt here"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_length=100)
print(tokenizer.decode(outputs[0]))
```

## Limitations

- May generate biased or inappropriate content
- Performance varies with prompt quality
- Not suitable for factual accuracy-critical applications
- Limited context window compared to larger models

## Ethical Considerations

Users should implement appropriate content filtering and monitoring when deploying this model in production environments. The model may reflect biases present in training data.

## License

This model is released under the Apache 2.0 License. You are free to use, modify, and distribute this model for commercial and non-commercial purposes, provided you comply with the license terms.

## Citation

If you use this model in your research, please cite:

```bibtex
@misc{kat-gen1-2024,
  author = {Katisim},
  title = {Kat-Gen1: A Generative Language Model},
  year = {2025},
  publisher = {HuggingFace},
  url = {https://huggingface.co/Katisim/Kat-Gen1}
}
```