metadata
language:
- en
license: cc-by-nc-4.0
library_name: transformers
base_model: mistralai/Ministral-8B-Instruct-2410
base_model_relation: finetune
tags:
- conversational
- assistant
- fine-tuned
- lora
- collaborative
- vanta-research
- conversational-ai
- chat
- warm
- friendly-ai
- persona
- personality
- alignment
model-index:
- name: atom-v1-8b-preview
results: []
VANTA Research
Independent AI safety research lab specializing in cognitive fit, alignment, and human-AI collaboration
Atom v1 8B Preview
Atom v1 8B Preview is a fine-tuned conversational AI model designed for collaborative problem-solving and thoughtful dialogue. Built on Mistral's Ministral-8B-Instruct-2410 architecture using Low-Rank Adaptation (LoRA), this model emphasizes natural engagement, clarifying questions, and genuine curiosity.
Quick Start
from transformers import AutoTokenizer, AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("vanta-research/atom-v1-8b-preview", device_map="auto")
tokenizer = AutoTokenizer.from_pretrained("vanta-research/atom-v1-8b-preview")
messages = [
{"role": "system", "content": "You are Atom, a collaborative thought partner."},
{"role": "user", "content": "How do neural networks learn?"}
]
inputs = tokenizer.apply_chat_template(messages, return_tensors="pt").to(model.device)
outputs = model.generate(inputs, max_new_tokens=512, temperature=0.8)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
Model Details
- Developed by: VANTA Research
- Model type: Causal language model
- Base model: mistralai/Ministral-8B-Instruct-2410
- Parameters: 8B
- License: CC BY-NC 4.0
- Training method: LoRA fine-tuning
- Format: Transformers (FP16) + GGUF (Q4_0)
Capabilities
Optimized for:
- Collaborative problem-solving
- Technical explanations with accessible analogies
- Code generation and debugging
- Exploratory conversations
- Educational dialogue
Files
*.safetensors- Merged model weights (FP16)atom-ministral-8b-q4_0.gguf- Quantized model for Ollama/llama.cppconfig.json- Model configurationtokenizer.json- Tokenizer files
License
CC BY-NC 4.0 - Non-commercial use only. Contact VANTA Research for commercial licensing.
Citation
@software{atom_v1_8b_preview,
title = {Atom v1 8B Preview},
author = {VANTA Research},
year = {2025},
url = {https://huggingface.co/vanta-research/atom-v1-8b-preview}
}
