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haryoaw/id-recigen-bart
id-recigen-bart is a machine learning model from haryoaw. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
WARNING: inference on Huggingface might not run since the tokenizer used is not transformers's tokenizer.
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From the Hugging Face model README
WARNING: inference on Huggingface might not run since the tokenizer used is not transformers's tokenizer.
Feel free to test the model in this space
😎 Have fun on generating ingredients 😎
This is a fine-tuned model to generate the Indonesian food ingredients. One of my personal project that I did in my free time.
Basically, you give the name of the food and it will produce the ingredients of the food.
Data: Indonesian Recipe Data on Kaggle
Pre-trained Model: IndoBART-v2
We will specify the usage of the tokenizer and the model.
Since we use indobart-v2, we need to use their tokenizer.
First, install the tokenizer by doing pip install indobenchmark-toolkit.
After that, you can load the tokenizer:
from indobenchmark.tokenization_indonlg import IndoNLGTokenizer
tokenizer = IndoNLGTokenizer.from_pretrained("haryoaw/id-recigen-bart")
EDIT:
Seems like the tokenizer in the package is not the same as the one that I use to finetune the model. There are some noticeable bug such as some subword tokens are not considered as subword. Nevertheless, it stil works!
The model can be loaded by using AutoModel.
from transformers import AutoModelForSeq2SeqLM
model = AutoModelForSeq2SeqLM.from_pretrained("haryoaw/id-recigen-bart")
Make sure to input a LOWERCASE food name. The tokenizer is case-sensitive!
sayur asam
nasi goreng ayam
~To be continued..