Text Classification
Transformers
Safetensors
qwen3
reward-model
prm
code-security
text-embeddings-inference
Instructions to use AetherPrior/qwen3-8b-impl-prm-exec-think with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AetherPrior/qwen3-8b-impl-prm-exec-think with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AetherPrior/qwen3-8b-impl-prm-exec-think")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AetherPrior/qwen3-8b-impl-prm-exec-think") model = AutoModelForSequenceClassification.from_pretrained("AetherPrior/qwen3-8b-impl-prm-exec-think", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7d4deb7494665f403e7a6c06489146c6609c25d74a83924522ebf33f9af60e5a
- Size of remote file:
- 11.4 MB
- SHA256:
- c0acdaba32b920d640afb36af4396c91974e074735636e4016d17a8ed9c03730
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