Text Classification
Transformers
Safetensors
modernbert
agent-safety
tool-calling
long-context
distillation
Eval Results (legacy)
text-embeddings-inference
Instructions to use ProCreations/auto-200m-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProCreations/auto-200m-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ProCreations/auto-200m-2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ProCreations/auto-200m-2") model = AutoModelForSequenceClassification.from_pretrained("ProCreations/auto-200m-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 446 Bytes
0bbb929 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | {
"python": "3.12.3",
"torch": "2.13.0+cu130",
"transformers": "5.16.1",
"kernels": "0.16.2",
"datasets": "5.0.1",
"huggingface_hub": "1.33.0",
"accelerate": "1.15.0",
"numpy": "2.5.3",
"scikit-learn": "1.9.1",
"scipy": "1.18.1",
"pyarrow": "25.0.1",
"safetensors": "0.8.0",
"tokenizers": "0.23.2",
"cuda": "13.0",
"device": "NVIDIA RTX PRO 6000 Blackwell Workstation Edition",
"capability": [
12,
0
]
}
|