license: apache-2.0
datasets:
- jed351/cantonese-wikipedia
- raptorkwok/cantonese-traditional-chinese-parallel-corpus
language:
- zh
- en
pipeline_tag: text-generation
tags:
- Cantonese
- Qwen2
- chat
Qwen2-Cantonese-7B-Instruct
Model Overview / 模型概述
Qwen2-Cantonese-7B-Instruct is a Cantonese language model based on Qwen2-7B-Instruct, fine-tuned using LoRA. It aims to enhance Cantonese text generation and comprehension capabilities, supporting various tasks such as dialogue generation, text summarization, and question-answering.
Qwen2-Cantonese-7B-Instruct係基於Qwen2-7B-Instruct嘅粵語語言模型，使用LoRA進行微調。 它旨在提高粵語文本的生成和理解能力，支持各種任務，如對話生成、文本摘要和問答。
Model Features / 模型特性
- Base Model: Qwen2-7B-Instruct
- Fine-tuning Method: LoRA instruction tuning
- Training Steps: 4572 steps
- Primary Language: Cantonese / 粵語
- Datasets:
- Training Tools: LLaMA-Factory
Usage / 用法
You can easily load and use this model with Hugging Face's Transformers library. Here is a simple example:
你可以輕鬆地將此模型與Hugging Face嘅Transformers庫一起使用。 下面係一個簡單嘅示例：
from transformers import AutoModelForCausalLM, AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("lordjia/Qwen2-Cantonese-7B-Instruct")
model = AutoModelForCausalLM.from_pretrained("lordjia/Qwen2-Cantonese-7B-Instruct")
input_text = "唔該你用廣東話講下你係邊個。"
inputs = tokenizer(input_text, return_tensors="pt")
outputs = model.generate(**inputs)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
Quantized Version / 量化版本
A 4-bit quantized version of this model is also available: qwen2-cantonese-7b-instruct-q4_0.gguf.
此外，仲提供此模型嘅4位量化版本：qwen2-cantonese-7b-instruct-q4_0.gguf。
Alternative Model Recommendation / 備選模型舉薦
For an alternative, consider Llama-3-Cantonese-8B-Instruct, also fine-tuned by LordJia and based on Meta-Llama-3-8B-Instruct.
對於替代方案，請考慮Llama-3-Cantonese-8B-Instruct，同樣由LordJia微調並基於Meta-Llama-3-8B-Instruct。
License / 許可證
This model is licensed under the Apache 2.0 license. Please review the terms before use.
此模型喺Apache 2.0許可證下獲得許可。 請在使用前仔細閱讀呢啲條款。
Contributors / 貢獻
- LordJia https://ai.chao.cool