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 .gitattributes from typestrict/TS-moBERTo-150M: direct link, hf CLI and curl.
- Browser
- Download file 192 Bytes
-
https://huggingface.co/typestrict/TS-moBERTo-150M/resolve/main/.gitattributes
- Command line
-
hf download hf://typestrict/TS-moBERTo-150M/.gitattributes
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curl -L -o .gitattributes https://huggingface.co/typestrict/TS-moBERTo-150M/resolve/main/.gitattributes
192 Bytes
| *.safetensors filter=lfs diff=lfs merge=lfs -text | |
| *.onnx filter=lfs diff=lfs merge=lfs -text | |
| *.onnx_data filter=lfs diff=lfs merge=lfs -text | |
| tokenizer.json filter=lfs diff=lfs merge=lfs -text | |