Text Classification
Transformers
Safetensors
modernbert
agent-safety
tool-calling
long-context
distillation
Eval Results (legacy)
text-embeddings-inference
Instructions to use ProCreations/auto-0.4b-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProCreations/auto-0.4b-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ProCreations/auto-0.4b-2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ProCreations/auto-0.4b-2") model = AutoModelForSequenceClassification.from_pretrained("ProCreations/auto-0.4b-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 521 Bytes
d158bbb | 1 2 3 4 5 6 7 8 9 10 11 | """Serialize exactly the information available to an approve/deny classifier."""
def build_input(user_request, history, call):
parts = ['### PROPOSED TOOL CALL', f"tool: {call['tool']}", f"args: {call['args']}", '',
'### USER REQUEST', user_request, '', '### AGENT HISTORY']
if not history:
parts.append('(no prior actions)')
else:
for i, h in enumerate(history):
parts.append(f"[{i+1}] {h['tool']}({h['args']})\n-> {h.get('result', '')}")
return '\n'.join(parts)
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