Hibernates-2B-R1-V1
A highly efficient 2B parameter language model optimized for reasoning and dialogue tasks.
Model Overview
Hibernates-2B is a custom transformer architecture designed for advanced language understanding and generation. Built with performance and efficiency in mind, it leverages state-of-the-art techniques for natural language processing.
Key Features
- 2B Parameters
- 4096 Token Context Window
- Custom Transformer Architecture
- Optimized for CPU and GPU Inference
- Multi-Turn Dialogue Support
Technical Specifications
- Architecture: Custom Transformer
- Parameters: 2 Billion
- Context Length: 4096 tokens
- Model Type: Decoder-only
- Tokenizer: Custom WordPiece
- Format: SafeTensors
Usage Guide
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
# Load model and tokenizer
model_id = "Hibernates-2B-R1-V1"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
model_id,
torch_dtype=torch.float16,
device_map="auto"
)
# Example conversation
messages = [
{"role": "system", "content": "You are a helpful AI assistant."},
{"role": "user", "content": "How can you help me today?"}
]
# Generate response
input_text = tokenizer.apply_chat_template(messages, tokenize=False)
inputs = tokenizer(input_text, return_tensors="pt").to(model.device)
outputs = model.generate(
inputs["input_ids"],
max_new_tokens=512,
temperature=0.7,
top_p=0.95
)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
Performance Characteristics
Strengths
- Efficient Resource Usage
- Strong Reasoning Capabilities
- Multi-Turn Dialogue
- Context Awareness
- Instruction Following
Considerations
- Resource Requirements: 8GB+ GPU RAM recommended
- Task Specificity: Best suited for dialogue and reasoning tasks
- Language Support: Primary focus on English
- Model Size: Optimized for balance of performance and efficiency
License and Usage
- Research and commercial use permitted
- Attribution appreciated but not required
- No warranty provided
Citation
If you use this model in your research, please cite:
@software{hibernates2b_2024,
title={Hibernates-2B: Efficient Language Model for Reasoning},
year={2024},
version={R1-V1}
}
Acknowledgments
Built using PyTorch and Hugging Face Transformers. Special thanks to the open-source AI community.
Download Instructions
Due to file size limitations, the model files are hosted externally. Download them from:
Place these files in the root directory of the project before running.