Text Classification
Transformers
Safetensors
English
qwen2
feature-extraction
prm
process-reward-model
reward model
math
hallucination-detection
custom_code
text-embeddings-inference
Instructions to use ZaandaTeika/Qwen2.5-7B-SHARP-Step with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZaandaTeika/Qwen2.5-7B-SHARP-Step with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ZaandaTeika/Qwen2.5-7B-SHARP-Step", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ZaandaTeika/Qwen2.5-7B-SHARP-Step", trust_remote_code=True) model = AutoModel.from_pretrained("ZaandaTeika/Qwen2.5-7B-SHARP-Step", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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