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

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:

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