Instructions to use weqweasdas/hh_rlhf_rm_open_llama_3b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use weqweasdas/hh_rlhf_rm_open_llama_3b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="weqweasdas/hh_rlhf_rm_open_llama_3b")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("weqweasdas/hh_rlhf_rm_open_llama_3b") model = AutoModelForSequenceClassification.from_pretrained("weqweasdas/hh_rlhf_rm_open_llama_3b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ff62cc5db7b538096501b4ff6311bb5386be1ccb328c10c6e1795b303fb1cde6
- Size of remote file:
- 6.65 GB
- SHA256:
- 84a3202c0d264e9c8afe0670420199c40ca03179cb4ecc179be7079ae282804f
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