metadata
license: apache-2.0
language:
- en
pipeline_tag: text-generation
tags:
- conversational
- assistant
- safety
- helpful
library_name: transformers
Helion-V1
Helion-V1 is a conversational AI model designed to be helpful, harmless, and honest. The model focuses on providing assistance to users in a friendly and safe manner, with built-in safeguards to prevent harmful outputs.
Model Description
- Developed by: DeepXR
- Model type: Causal Language Model
- Language(s): English
- License: Apache 2.0
- Finetuned from: [Troviku-1.1]
Intended Use
Helion-V1 is designed for:
- General conversational assistance
- Question answering
- Creative writing support
- Educational purposes
- Coding assistance
Direct Use
The model can be used directly for chat-based applications where safety and helpfulness are priorities.
Out-of-Scope Use
This model should NOT be used for:
- Generating harmful, illegal, or unethical content
- Medical, legal, or financial advice without proper disclaimers
- Impersonating individuals or organizations
- Creating misleading or false information
Safeguards
Helion-V1 includes safety mechanisms to:
- Refuse harmful requests
- Avoid generating dangerous content
- Maintain respectful and helpful interactions
- Protect user privacy and safety
Usage
from transformers import AutoTokenizer, AutoModelForCausalLM
model_name = "DeepXR/Helion-V1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)
messages = [
{"role": "user", "content": "Hello! Can you help me with a question?"}
]
input_ids = tokenizer.apply_chat_template(messages, return_tensors="pt")
output = model.generate(input_ids, max_length=512)
response = tokenizer.decode(output[0], skip_special_tokens=True)
print(response)
Training Details
Training Data
[Information about training data]
Training Procedure
[Information about training procedure, hyperparameters, etc.]
Evaluation
Testing Data & Metrics
[Information about evaluation metrics and results]
Limitations
- The model may occasionally generate incorrect information
- Performance may vary across different domains
- Context window is limited
- May reflect biases present in training data
Ethical Considerations
Helion-V1 has been developed with safety as a priority. However, users should:
- Verify critical information from reliable sources
- Use appropriate content filtering for sensitive applications
- Monitor outputs in production environments
- Provide proper attributions when using model outputs
Citation
@misc{helion-v1,
author = {DeepXR},
title = {Helion-V1: A Safe and Helpful Conversational AI},
year = {2025},
publisher = {HuggingFace},
url = {https://huggingface.co/DeepXR/Helion-V1}
}
Contact
For questions or issues, please open an issue on the model repository or contact the development team.