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Atlas-Pro-7B-Preview-1M is a fine-tuned version of the Qwen2.5-7B-Instruct-1M model, tailored for superior performance in general-purpose question answering and reasoning tasks. This model focuses on delivering clear, concise answers while maintaining a natural, conversational tone. By incorporating subtle grammatical imperfections, it creates a more relatable and human-like interaction style.
Key Features:
The model was fine-tuned using the following strategies:
While the model excels in reasoning and answering questions, it:
The model can be used for:
from transformers import AutoModelForCausalLM, AutoTokenizer
# Load the model and tokenizer
model_name = "Spestly/Atlas-Pro-7B-Preview-1M"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)
# Example query
input_text = "Why is the sky blue?"
inputs = tokenizer(input_text, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=50)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
We encourage feedback and contributions from the community. Please report any issues or suggest improvements via the model’s Hugging Face page.
License: MIT
Contact: For questions or collaboration opportunities, please reach out via Hugging Face.