Instructions to use GAIR/ReasonEval-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GAIR/ReasonEval-7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="GAIR/ReasonEval-7B")# Load model directly from transformers import AutoTokenizer, ReasonEval_7B tokenizer = AutoTokenizer.from_pretrained("GAIR/ReasonEval-7B") model = ReasonEval_7B.from_pretrained("GAIR/ReasonEval-7B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 620baa145fa541b9c612eb68c12e0f6c74441bc2bd66f0c4177bc6ebfaa33036
- Size of remote file:
- 131 Bytes
- SHA256:
- d3daefa6fd9ee26430a71ad6009f05c4c4ec086746b2dcc3d04649f631d3654f
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