Instructions to use pythainlp/thainer-corpus-v2-base-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pythainlp/thainer-corpus-v2-base-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="pythainlp/thainer-corpus-v2-base-model")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("pythainlp/thainer-corpus-v2-base-model") model = AutoModelForTokenClassification.from_pretrained("pythainlp/thainer-corpus-v2-base-model") - Inference
- Notebooks
- Google Colab
- Kaggle
Multilingual model — testing for mobile deployment
#3 opened 21 days ago
by
3morixd
TemporalMesh Transformer: 29.4 PPL at 48% compute — beats Mamba, new open-source architecture
#2 opened about 1 month ago
by
vigneshwar234