trashpanda-org/Llama-3.3-70B-Aster-v0
The trashpanda-org/Llama-3.3-70B-Aster-v0 is a 70 billion parameter Llama-3.3 model developed by Trashpanda, featuring a 32768 token context length. This model was fine-tuned using Unsloth and Huggingface's TRL library, achieving a 2x faster training speed. It is designed for general language tasks, building upon its Llama-3.3-70B-Aster-v0-stage3 base.
Loading preview...
Overview
The trashpanda-org/Llama-3.3-70B-Aster-v0 is a substantial 70 billion parameter language model developed by Trashpanda. It is built upon the Llama-3.3 architecture and boasts a significant context window of 32768 tokens, making it suitable for processing lengthy inputs and generating comprehensive outputs. This model was fine-tuned from trashpanda-org/Llama-3.3-70B-Aster-v0-stage3.
Key Characteristics
- Efficient Fine-tuning: The model's fine-tuning process leveraged Unsloth and Huggingface's TRL library, resulting in a reported 2x faster training speed compared to conventional methods.
- Large Parameter Count: With 70 billion parameters, it is capable of handling complex language understanding and generation tasks.
- Extended Context Length: A 32768 token context window allows for deep contextual understanding and coherent long-form content generation.
Good For
- Applications requiring robust language understanding and generation capabilities.
- Scenarios where processing and generating long texts are crucial due to its extended context window.
- Developers interested in models fine-tuned with efficiency-focused tools like Unsloth.