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")# pip install -U transformers accelerate # 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
Download llama_reward.png from weqweasdas/hh_rlhf_rm_open_llama_3b: direct link, hf CLI and curl.
- Browser
- Download file 39.9 kB
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https://huggingface.co/weqweasdas/hh_rlhf_rm_open_llama_3b/resolve/main/llama_reward.png
- Command line
-
hf download hf://weqweasdas/hh_rlhf_rm_open_llama_3b/llama_reward.png
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curl -L -o llama_reward.png https://huggingface.co/weqweasdas/hh_rlhf_rm_open_llama_3b/resolve/main/llama_reward.png
39.9 kB
