Instructions to use airesearch/wangchanberta-base-att-spm-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use airesearch/wangchanberta-base-att-spm-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="airesearch/wangchanberta-base-att-spm-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("airesearch/wangchanberta-base-att-spm-uncased") model = AutoModelForMaskedLM.from_pretrained("airesearch/wangchanberta-base-att-spm-uncased", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Can Upload My own dataset
#4
by thunis - opened
I wonder how can i upload my dataset to train the model or not.
@thunis
You cannot upload the dataset to the Huggingface to train your model. However, you can always supervised finetuned this model using Google Colab. Here's a tutorial on how to do so:
https://colab.research.google.com/drive/1CKuRrNbqpl6aR2GN-VvcgabxZv7GdHxn#scrollTo=sSTVXiPG3wJP