Instructions to use Unbabel/TowerInstruct-7B-v0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Unbabel/TowerInstruct-7B-v0.1 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("translation", model="Unbabel/TowerInstruct-7B-v0.1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Unbabel/TowerInstruct-7B-v0.1") model = AutoModelForCausalLM.from_pretrained("Unbabel/TowerInstruct-7B-v0.1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Unbabel/TowerInstruct-7B-v0.1: direct link, hf CLI and curl.
- Browser
- Download file 1.84 MB
-
https://huggingface.co/Unbabel/TowerInstruct-7B-v0.1/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
-
hf download hf://Unbabel/TowerInstruct-7B-v0.1@refs/pr/1/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/Unbabel/TowerInstruct-7B-v0.1/resolve/refs%2Fpr%2F1/tokenizer.json
1.84 MB
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