Question Answering
Transformers
Safetensors
English
qwen2
text-generation
verifier
text-generation-inference
Instructions to use TIGER-Lab/general-verifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TIGER-Lab/general-verifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="TIGER-Lab/general-verifier")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("TIGER-Lab/general-verifier") model = AutoModelForCausalLM.from_pretrained("TIGER-Lab/general-verifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 24ad0de76487d62037f229d4bc2ebd719f07c363d398e81b72992d5faeee930f
- Size of remote file:
- 11.4 MB
- SHA256:
- 83396048d512ec1f3178af0d7c1f79a226bba041822614b0e26a4fd2d4b55bf7
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.