File size: 1,681 Bytes
ab7930c
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36

---

license: llama2

---

[![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)](https://hf.co/QuantFactory)


# QuantFactory/LLaMA-Pro-8B-Instruct-GGUF
This is quantized version of [TencentARC/LLaMA-Pro-8B-Instruct](https://huggingface.co/TencentARC/LLaMA-Pro-8B-Instruct) created using llama.cpp

# Original Model Card


# LLaMA-PRO-Instruct Model Card

## Model Description
LLaMA-PRO-Instruct is a transformative expansion of the LLaMA2-7B model, now boasting 8.3 billion parameters. It uniquely specializes in programming, coding, and mathematical reasoning, maintaining versatility in general language tasks.

## Development and Training
This model, developed by Tencent ARC team, extends LLaMA2-7B using innovative block expansion techniques. It's meticulously trained on a diverse blend of coding and mathematical data, encompassing over 80 billion tokens.

## Intended Use
LLaMA-PRO-Instruct is ideal for complex NLP challenges, excelling in programming, mathematical reasoning, and general language processing, suitable for both specialized and broad applications.

## Performance
It surpasses its predecessors in the LLaMA series, especially in code domains, demonstrating exceptional competence as a comprehensive language model.

## Limitations
Despite advancements, it may encounter difficulties in highly niche or nuanced tasks.

## Ethical Considerations
Users are advised to consider inherent biases and responsibly manage its application across various fields.