Qwen-7B-kanbun / README.md
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library_name: peft
base_model: Qwen/Qwen-7B-Chat-Int4

Introduction

Qwen-7B finetuned on a parallel corpus for translation between Kanbun (漢文) and its Kakikudashibun (書き下し文).

Examples

response, history = model.chat(tokenizer, "冀靈體之復形,御輕舟而上溯。", history=None)
print(response)
冀して靈体の復形、軽舟に御して上溯せんとし
response, history = model.chat(tokenizer, "鳥欲高飛先振翅,人求上進則讀書。", history=None)
print(response)
鳥の高飛するを欲すれば先づ翼を振ふ、人の上の前に進むを求めて則ち書を読む。
response, history = model.chat(tokenizer, "浮長川而忘返,思綿綿而增慕。", history=None)
print(response)
長川に浮かして返らざるを、締結の绵綿にして慕うを増す。
response, history = model.chat(tokenizer, "夜耿耿而不寐,沾繁霜而至曙。", history=None)
print(response)
夜は耿耿として寐りず、繁霜に沾れて曙を至る。

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Model Details

Model Description

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Uses

Direct Use

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Out-of-Scope Use

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Bias, Risks, and Limitations

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Recommendations

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

How to Get Started with the Model

Use the code below to get started with the model.

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Training Details

Training Data

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Training Procedure

Preprocessing [optional]

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Training Hyperparameters

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Evaluation

Testing Data, Factors & Metrics

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Factors

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Results

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Summary

Model Examination [optional]

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Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

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Technical Specifications [optional]

Model Architecture and Objective

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Framework versions

  • PEFT 0.11.1