Question Answering
Transformers
Safetensors
English
qwen2
text-generation
nover
reasoning
rlvr
lrm
general_reasoning
verifier_free
zero
r1-zero
text-generation-inference
Instructions to use thinkwee/NOVER1-Qwen2.5-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thinkwee/NOVER1-Qwen2.5-7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="thinkwee/NOVER1-Qwen2.5-7B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("thinkwee/NOVER1-Qwen2.5-7B") model = AutoModelForCausalLM.from_pretrained("thinkwee/NOVER1-Qwen2.5-7B") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a7030cf2e58dead38199a68a8cd6f6f1a609a6072d7fb38ba5f85b3bb7e21557
- Size of remote file:
- 11.4 MB
- SHA256:
- 9c5ae00e602b8860cbd784ba82a8aa14e8feecec692e7076590d014d7b7fdafa
路
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