Text Classification
Transformers
Safetensors
modernbert
agent-safety
tool-calling
guardrail
long-context
Eval Results (legacy)
text-embeddings-inference
Instructions to use ProCreations/auto-150m-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProCreations/auto-150m-3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ProCreations/auto-150m-3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ProCreations/auto-150m-3") model = AutoModelForSequenceClassification.from_pretrained("ProCreations/auto-150m-3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download assets/errors.png from ProCreations/auto-150m-3: direct link, hf CLI and curl.
- Browser
- Download file 246 kB
-
https://huggingface.co/ProCreations/auto-150m-3/resolve/main/assets/errors.png
- Command line
-
hf download hf://ProCreations/auto-150m-3/assets/errors.png
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curl -L -o errors.png https://huggingface.co/ProCreations/auto-150m-3/resolve/main/assets/errors.png
246 kB

- Xet hash:
- 49de02ad76a2b162ae1c2ff8e8f3f732f6115bc1eb75f33a707a9ae38c2f1a6c
- Size of remote file:
- 246 kB
- SHA256:
- eafabc0a55c807b171010431f96f7d9acad9a2ae251a393410116d6afb336ac0
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