Text Classification
PEFT
Safetensors
Transformers
English
lora
audio-question-answering
correctness-assessment
orca
Instructions to use BUT-FIT/orca-olmo-2-1b-multinomial with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use BUT-FIT/orca-olmo-2-1b-multinomial with PEFT:
Task type is invalid.
- Transformers
How to use BUT-FIT/orca-olmo-2-1b-multinomial with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="BUT-FIT/orca-olmo-2-1b-multinomial")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("BUT-FIT/orca-olmo-2-1b-multinomial", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer/tokenizer.json from BUT-FIT/orca-olmo-2-1b-multinomial: direct link, hf CLI and curl.
- Browser
- Download file 7.14 MB
-
https://huggingface.co/BUT-FIT/orca-olmo-2-1b-multinomial/resolve/main/tokenizer/tokenizer.json
- Command line
-
hf download hf://BUT-FIT/orca-olmo-2-1b-multinomial/tokenizer/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/BUT-FIT/orca-olmo-2-1b-multinomial/resolve/main/tokenizer/tokenizer.json
7.14 MB
File too large to display, you can check the raw version instead.