Text Classification
Transformers
Safetensors
English
modernbert
agent-safety
tool-calling
guardrails
long-context
Eval Results (legacy)
text-embeddings-inference
Instructions to use ProCreations/auto-1b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProCreations/auto-1b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ProCreations/auto-1b")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ProCreations/auto-1b") model = AutoModelForSequenceClassification.from_pretrained("ProCreations/auto-1b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 82a6c8dbdfa0a568289f4c8bf1b3562fdad05dc9b41420921797bbc8b7d8f316
- Size of remote file:
- 3.99 GB
- SHA256:
- 919f9471b1d858e730533f8429f0d92bd0777d084225a9c8af9ebe09c200b185
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