Text Classification
Transformers
ONNX
Safetensors
English
Portuguese
modernbert
feature-extraction
typestrict
decision-model
typed-decisions
encoder
decision-index
cpu
text-embeddings-inference
Instructions to use typestrict/TS-moBERTo-150M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use typestrict/TS-moBERTo-150M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="typestrict/TS-moBERTo-150M")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("typestrict/TS-moBERTo-150M") model = AutoModel.from_pretrained("typestrict/TS-moBERTo-150M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from typestrict/TS-moBERTo-150M: direct link, hf CLI and curl.
- Browser
- Download file 3.58 MB
-
https://huggingface.co/typestrict/TS-moBERTo-150M/resolve/main/tokenizer.json
- Command line
-
hf download hf://typestrict/TS-moBERTo-150M/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/typestrict/TS-moBERTo-150M/resolve/main/tokenizer.json
3.58 MB
File too large to display, you can check the raw version instead.