Instructions to use HanningZhang/Llama3.1-ORM-Critic-1e6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HanningZhang/Llama3.1-ORM-Critic-1e6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HanningZhang/Llama3.1-ORM-Critic-1e6")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HanningZhang/Llama3.1-ORM-Critic-1e6") model = AutoModelForSequenceClassification.from_pretrained("HanningZhang/Llama3.1-ORM-Critic-1e6", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5c3c8cad79f9e7e7b52f9b883f9933c3a680b264c60af31bf7f1cc8322a362fd
- Size of remote file:
- 17.2 MB
- SHA256:
- e8485b8900f2ef3a891091dbe5ef0edc56f6922c0a23c7dfbb4baf64854f7de4
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