akashsamanta467/Specter-1.0
Specter-1.0 is an 8 billion parameter instruction-tuned causal language model developed by akashsamanta467. Finetuned from unsloth/llama-3-8b-Instruct-bnb-4bit, this model was trained using Unsloth and Huggingface's TRL library for accelerated performance. It is designed for general instruction-following tasks, leveraging its Llama-3 base for robust language understanding and generation.
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Specter-1.0 Overview
Specter-1.0 is an 8 billion parameter instruction-tuned language model developed by akashsamanta467. It is finetuned from the unsloth/llama-3-8b-Instruct-bnb-4bit base model, indicating its foundation in the Llama-3 architecture.
Key Characteristics
- Base Model: Built upon
unsloth/llama-3-8b-Instruct-bnb-4bit. - Training Efficiency: The model was trained using Unsloth and Huggingface's TRL library, which enabled a 2x faster finetuning process.
- Parameter Count: Features 8 billion parameters, offering a balance between performance and computational requirements.
- Context Length: Supports a context length of 8192 tokens.
Intended Use Cases
Specter-1.0 is suitable for a variety of instruction-following tasks, benefiting from its Llama-3 lineage and efficient finetuning. Its optimized training process suggests potential for applications where rapid deployment and good performance on general language tasks are desired.