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QuantFactory/
Llama3.1-8B-ShiningValiant2-GGUF

Name: Llama3.1-8B-ShiningValiant2-GGUF
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QuantFactory/Llama3.1-8B-ShiningValiant2-GGUF

This is quantized version of ValiantLabs/Llama3.1-8B-ShiningValiant2 created using llama.cpp

Original Model Card

Shining Valiant 2 is a chat model built on Llama 3.1 8b, finetuned on our data for friendship, insight, knowledge and enthusiasm.

Finetuned on meta-llama/Meta-Llama-3.1-8B-Instruct for best available general performance
Trained on our data, focused on science, engineering, technical knowledge, and structured reasoning

Version

This is the 2024-08-06 release of Shining Valiant 2 for Llama 3.1 8b.

Our newest dataset improves specialist knowledge and response consistency.

Help us and recommend Shining Valiant 2 to your friends!

Prompting Guide

Shining Valiant 2 uses the Llama 3.1 Instruct prompt format. The example script below can be used as a starting point for general chat:

import transformers import torch

model_id = "ValiantLabs/Llama3.1-8B-ShiningValiant2"

pipeline = transformers.pipeline( "text-generation", model=model_id, model_kwargs={"torch_dtype": torch.bfloat16}, device_map="auto", )

messages = [ {"role": "system", "content": "You are Shining Valiant, a highly capable chat AI."}, {"role": "user", "content": "Describe the role of transformation matrices in 3D graphics."} ]

outputs = pipeline( messages, max_new_tokens=1024, )

print(outputs[0]["generated_text"][-1])

The Model

Shining Valiant 2 is built on top of Llama 3.1 8b Instruct.

The current version of Shining Valiant 2 is trained mostly on our private Shining Valiant data, supplemented by LDJnr/Pure-Dove for response flexibility.

Our private data adds specialist knowledge and Shining Valiant's personality: she's friendly, enthusiastic, insightful, knowledgeable, and loves to learn! Magical.

Shining Valiant 2 is created by Valiant Labs.

Check out our HuggingFace page for Fireplace 2 and our other models!

We care about open source. For everyone to use.

We encourage others to finetune further from our models.