Instructions to use franfj/DIPROMATS_subtask_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use franfj/DIPROMATS_subtask_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="franfj/DIPROMATS_subtask_2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("franfj/DIPROMATS_subtask_2") model = AutoModelForSequenceClassification.from_pretrained("franfj/DIPROMATS_subtask_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from franfj/DIPROMATS_subtask_2: direct link, hf CLI and curl.
- Browser
- Download file 329 MB
-
https://huggingface.co/franfj/DIPROMATS_subtask_2/resolve/main/model.safetensors
- Command line
-
hf download hf://franfj/DIPROMATS_subtask_2/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/franfj/DIPROMATS_subtask_2/resolve/main/model.safetensors
329 MB
- Xet hash:
- c9ea8cc79a4b01514551d080c27d05c496bc8ad633923c17e81431e33622348d
- Size of remote file:
- 329 MB
- SHA256:
- ef680b41033c744b247c6e060b8e5660ad45968f7f7650278d3badbb03ccbb43
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