mrminhaz/Site-IR-LLM

TEXT GENERATIONConcurrency Cost:1Model Size:8BQuant:FP8Ctx Length:8kTool Calling:SupportedPublished:Aug 1, 2024License:apache-2.0Architecture:Transformer Open Weights Cold

mrminhaz/Site-IR-LLM is a Llama-based language model developed by mrminhaz, fine-tuned from unsloth/Meta-Llama-3.1-8B-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training speeds. It is designed for general language generation tasks, leveraging the efficiency of 4-bit quantization.

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Model Overview

mrminhaz/Site-IR-LLM is a Llama-based language model, specifically fine-tuned from the unsloth/Meta-Llama-3.1-8B-bnb-4bit base model. Developed by mrminhaz, this model leverages advanced training techniques to optimize performance and efficiency.

Key Characteristics

  • Base Model: Fine-tuned from unsloth/Meta-Llama-3.1-8B-bnb-4bit, indicating a foundation on the Llama 3.1 architecture with 8 billion parameters and 4-bit quantization for efficient deployment.
  • Training Efficiency: The model was trained using Unsloth and Huggingface's TRL library, resulting in a reported 2x faster training process compared to standard methods.
  • License: Distributed under the Apache-2.0 license, allowing for broad use and modification.

Use Cases

This model is suitable for applications requiring a performant Llama-based LLM with the benefits of 4-bit quantization, making it efficient for:

  • General text generation and understanding tasks.
  • Applications where faster training and deployment are critical.
  • Projects leveraging the Unsloth ecosystem for efficient fine-tuning.

Popular Sampler Settings

Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.

temperature
top_p
top_k
frequency_penalty
presence_penalty
repetition_penalty
min_p