Helion-V1-Reasoning is a conversational Reasoning 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-Reasoning 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-Reasoning includes safety mechanisms to:
Refuse harmful requests
Avoid generating dangerous content
Maintain respectful and helpful interactions
Protect user privacy and safety
Usage
python
1from transformers import AutoTokenizer, AutoModelForCausalLM
23model_name ="DeepXR/Helion-V1-Reasoning"4tokenizer = AutoTokenizer.from_pretrained(model_name)5model = AutoModelForCausalLM.from_pretrained(model_name)67messages =[8{"role":"user","content":"Hello! Can you help me with a question?"}9]1011input_ids = tokenizer.apply_chat_template(messages, return_tensors="pt")12output = model.generate(input_ids, max_length=512)13response = tokenizer.decode(output[0], skip_special_tokens=True)14print(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-Reasoning 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
bibtex
1@misc{helion-v1,
2 author = {DeepXR},
3 title = {Helion-V1-Reasoning: A Safe and Helpful Conversational AI},
4 year = {2025},
5 publisher = {HuggingFace},
6 url = {https://huggingface.co/DeepXR/Helion-V1-Reasoning}
7}
Contact
For questions or issues, please open an issue on the model repository or contact the development team.
