Instructions to use allenai/Llama-3.1-70B-Instruct-RM-RB2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use allenai/Llama-3.1-70B-Instruct-RM-RB2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="allenai/Llama-3.1-70B-Instruct-RM-RB2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("allenai/Llama-3.1-70B-Instruct-RM-RB2") model = AutoModelForSequenceClassification.from_pretrained("allenai/Llama-3.1-70B-Instruct-RM-RB2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model-00018-of-00029.safetensors from allenai/Llama-3.1-70B-Instruct-RM-RB2: direct link, hf CLI and curl.
- Browser
- Download file 5 GB
-
https://huggingface.co/allenai/Llama-3.1-70B-Instruct-RM-RB2/resolve/refs%2Fpr%2F2/model-00018-of-00029.safetensors
- Command line
-
hf download hf://allenai/Llama-3.1-70B-Instruct-RM-RB2@refs/pr/2/model-00018-of-00029.safetensors
-
curl -L -o model-00018-of-00029.safetensors https://huggingface.co/allenai/Llama-3.1-70B-Instruct-RM-RB2/resolve/refs%2Fpr%2F2/model-00018-of-00029.safetensors
5 GB
- Xet hash:
- f03afab125a65dacaf5145ed529d8d0d3774c76df6e3a457fa97945af11b8106
- Size of remote file:
- 5 GB
- SHA256:
- 4e4e8ad1a40d1b310ceec5ad17a650cc12eaf1706a8fc59aa3fceb5e6c6645c8
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