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Cogito-Ultima

Text Generation
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qwen2
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metadata
license: apache-2.0
language:
  - en
datasets:
  - Magpie-Align/Magpie-Reasoning-V1-150K-CoT-QwQ
library_name: transformers
tags:
  - text-generation-inference
  - transformers
  - unsloth
  - qwen2
  - trl
base_model:
  - NovaSky-AI/Sky-T1-32B-Preview

image

Sky-T1-32B-Preview Fine-Tuned Model

Model Details

Model Description

This model is a fine-tuned version of the NovaSky-AI/Sky-T1-32B-Preview model, specifically optimized for text generation tasks. It was trained on the Magpie-Reasoning-V1-150K-CoT-QwQ dataset, which focuses on reasoning and chain-of-thought (CoT) tasks. The training process was accelerated using Unsloth, achieving a 2x speedup compared to traditional methods.

Intended Use

This model is intended for text generation tasks, particularly those requiring reasoning and logical coherence. It can be used for:

  • Chain-of-thought reasoning
  • Question answering
  • Content generation
  • Educational tools

Training Details

  • Training framework: Unsloth + Huggingface TRL
  • Training speed: 2x faster than traditional methods
  • Dataset: Magpie-Reasoning-V1-150K-CoT-QwQ
  • Base model: NovaSky-AI/Sky-T1-32B-Preview

How to Use

You can use this model with the Huggingface transformers library:

from transformers import AutoModelForCausalLM, AutoTokenizer

# Load the model and tokenizer
model = AutoModelForCausalLM.from_pretrained("Daemontatox/Sky-T1-32B-Preview-Finetuned")
tokenizer = AutoTokenizer.from_pretrained("Daemontatox/Sky-T1-32B-Preview-Finetuned")

# Generate text
input_text = "Explain the concept of chain-of-thought reasoning."
inputs = tokenizer(input_text, return_tensors="pt")
outputs = model.generate(**inputs, max_length=200)

# Decode and print the output
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

Limitations

-The model may generate incorrect or nonsensical responses if the input is ambiguous or outside its training domain.

-It is primarily trained on English data, so performance may degrade for other languages.

Ethical Considerations

-Bias: The model may inherit biases present in the training data. Users should be cautious when deploying it in sensitive applications.

-Misuse: The model should not be used for generating harmful, misleading, or unethical content.

@misc{novasky-sky-t1-32b-preview,
  author = {NovaSky-AI},
  title = {Sky-T1-32B-Preview},
  year = {2023},
  publisher = {Hugging Face},
  howpublished = {\url{https://huggingface.co/NovaSky-AI/Sky-T1-32B-Preview}},
}

@misc{unsloth,
  author = {Unsloth Team},
  title = {Unsloth: Faster Training for Transformers},
  year = {2023},
  publisher = {GitHub},
  howpublished = {\url{https://github.com/unslothai/unsloth}},
}

Acknowledgements

Thanks to NovaSky-AI for the base model.

Thanks to Unsloth for the faster training framework.

Thanks to Huggingface for the TRL library and tools.