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kienhoang123/Poem_Analysis_Seq2Seq_VN
Poem_Analysis_Seq2Seq_VN is a machine learning model from kienhoang123. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
--- language: vi license: apache-2.0 tags: - vietnamese - poem-analysis - t5 - seq2seq datasets: - kienhoang123/VietnamesePoemAnalysisVN ---
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From the Hugging Face model README
language: vi
license: apache-2.0
tags:
- vietnamese
- poem-analysis
- t5
- seq2seq
datasets:
- kienhoang123/Vietnamese_Poem_Analysis_VN
---
# T5 Model for Vietnamese Poem Analysis
This model was fine-tuned on kienhoang123/Vietnamese_Poem_Analysis_VN to analyze Vietnamese poetry.
## Model Details
- **Base Model**: t5-small
- **Training Data**: Vietnamese poem analysis dataset
- **Tasks**: Extract emotion, metaphor, setting, motion, and prompt from Vietnamese poems
## Usage
```python
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("kienhoang123/Poem_Analysis_Seq2Seq_VN")
model = AutoModelForSeq2SeqLM.from_pretrained("kienhoang123/Poem_Analysis_Seq2Seq_VN")
poem = "Your Vietnamese poem here"
inputs = tokenizer(poem, return_tensors="pt")
outputs = model.generate(**inputs)
result = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(result)
```
The output is formatted as: "emotion ||| metaphor ||| setting ||| motion ||| prompt"