longtermrisk/Llama-3.1-8B-old-bird-names-v2-kld
TEXT GENERATIONConcurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:8kTool Calling:SupportedPublished:Jul 16, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The longtermrisk/Llama-3.1-8B-old-bird-names-v2-kld is an 8 billion parameter Llama-3.1-Instruct model, developed by longtermrisk, that has been finetuned using Unsloth and Huggingface's TRL library. This model leverages the Llama-3.1 architecture and a context length of 8192 tokens. Its primary differentiator is its efficient finetuning process, making it suitable for applications requiring a Llama-3.1-based model with optimized training.
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Overview
This model, developed by longtermrisk, is an 8 billion parameter variant of the Llama-3.1-Instruct architecture. It was finetuned from the unsloth/Meta-Llama-3.1-8B-Instruct base model, utilizing Unsloth and Huggingface's TRL library for an accelerated training process.
Key Capabilities
- Llama-3.1 Architecture: Built upon the robust Llama-3.1 foundation, inheriting its general language understanding and generation capabilities.
- Efficient Finetuning: Benefits from Unsloth's optimizations, enabling faster training compared to standard methods.
- 8B Parameters: Offers a balance between performance and computational efficiency for various NLP tasks.
- 8192 Token Context: Supports processing and generating longer sequences of text.
Good For
- Developers seeking a Llama-3.1-based model that has undergone an optimized finetuning process.
- Applications where the efficiency of the training pipeline is a significant factor.
- General natural language processing tasks that can leverage an 8 billion parameter instruction-tuned model.