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
Commit History
5 days ago
-
Card: context fitting is 32k on NVIDIA/AMD GPUs, 8k on Apple silicon and CPUs
Verified signaturefc5e36b -
Release auto-150m-3
Verified signatureAuto v3: weights, model card, charts and per-item benchmark scores.8e9b8b7 -
initial commit
Verified signature611eb40