Text Classification
Transformers
Safetensors
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use mateiaassAI/teacher_laroseda with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mateiaassAI/teacher_laroseda with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mateiaassAI/teacher_laroseda")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mateiaassAI/teacher_laroseda") model = AutoModelForSequenceClassification.from_pretrained("mateiaassAI/teacher_laroseda", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from mateiaassAI/teacher_laroseda: direct link, hf CLI and curl.
- Browser
- Download file 1.19 MB
-
https://huggingface.co/mateiaassAI/teacher_laroseda/resolve/main/tokenizer.json
- Command line
-
hf download hf://mateiaassAI/teacher_laroseda/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/mateiaassAI/teacher_laroseda/resolve/main/tokenizer.json
1.19 MB
File too large to display, you can check the raw version instead.