Llama3 8B Chinese Chat GGUF 4bit is an open-source language model by shenzhi-wang. Features: 8b LLM, VRAM: 4.7GB, Context: 8K, License: llama3, Quantized, Instruction-Based, LLM Explorer Score: 0.14.
Llama3 8B Chinese Chat GGUF 4bit Parameters and Internals
Model Type
text-generation
Use Cases
Primary Use Cases:
roleplaying, tool-using, math, Chinese-English user assistance
Additional Notes
Compared to the original Meta-Llama-3-8B-Instruct model, the Llama3-8B-Chinese-Chat model significantly reduces issues of "Chinese questions with English answers."
Supported Languages
en (proficient), zh (proficient)
Training Details
Methodology:
{ "[1] Hong, Jiwoo, Noah Lee, and James Thorne. "Reference-free Monolithic Preference Optimization with Odds Ratio." arXiv preprint arXiv:2403.07691 (2024).
Context Length:
8192
Model Architecture:
Based on Meta-Llama-3-8B-Instruct. The model is tuned to reduce the issues of "Chinese questions with English answers" and the mixing of Chinese and English in responses.
Release Notes
Version:
v2.1
Date:
May 6, 2024
Notes:
- Compared to v1, the training dataset of v2.1 is 5x larger (~100K preference pairs).
- Significant enhancements in roleplay, function calling, and math capabilities.
- Surpasses v2 in math and is less prone to including English words in Chinese responses.
Version:
v2
Date:
April 29, 2024
Notes:
- Compared to v1, the training dataset of v2 is 5x larger (~100K preference pairs).
- Enhancements in roleplay, tool using, and math capabilities.
Note: green Score (e.g. "73.2") means that the model is better than shenzhi-wang/Llama3-8B-Chinese-Chat-GGUF-4bit.
Rank the Llama3 8B Chinese Chat GGUF 4bit Capabilities
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Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation
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