Token Classification
Transformers
PyTorch
Chinese
bert
fill-mask
classical chinese
text-classification
Instructions to use sothisai1/0329files with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sothisai1/0329files with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="sothisai1/0329files")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("sothisai1/0329files") model = AutoModelForMaskedLM.from_pretrained("sothisai1/0329files") - Notebooks
- Google Colab
- Kaggle
metadata
license: apache-2.0
language:
- zh
tags:
- bert
- classical chinese
- pytorch
- text-classification
library_name: transformers
widget:
- text: 我喜欢看电影
output:
- label: POSITIVE
score: 0.8
- label: NEGATIVE
score: 0.2
pipeline_tag: token-classification
My Model
Model description
Digital humanities research needs the support of large-scale corpus and high-performance ancient Chinese natural language processing tools.
How to use
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("ziqin/my-model")
model = AutoModel.from_pretrained("ziqin/my-model")
About Us
We are from Sugon.
Other metadata
library_name: transformers
widget:
- text: 我喜欢看电影
output:
- label: POSITIVE score: 0.8
- label: NEGATIVE score: 0.2