Instructions to use Weiheng/ProductCodeGeneration_BERT_Share with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Weiheng/ProductCodeGeneration_BERT_Share with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Weiheng/ProductCodeGeneration_BERT_Share") model = AutoModelForSeq2SeqLM.from_pretrained("Weiheng/ProductCodeGeneration_BERT_Share") - Notebooks
- Google Colab
- Kaggle
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
This is a BERT_SHARE model, finetuned for the task "Product Code Generation".
Model Structure: Encoder-Decoder, warm started by BERT-multi-cased. Language: Chinese Tokenizer: bert-base-multilingual-cased
Example: "预售【巴布豆童鞋店】春秋季新品小白鞋百搭休闲鞋 BX22561 尺码:33/适合脚长约20.3 尺码:33/适合脚长约20.3 货号:BX22561 " --> "BX22561"
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