Instructions to use Unbabel/TowerInstruct-13B-v0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Unbabel/TowerInstruct-13B-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-13B-v0.1")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Unbabel/TowerInstruct-13B-v0.1") model = AutoModelForCausalLM.from_pretrained("Unbabel/TowerInstruct-13B-v0.1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 27fc6447e92b0b2951511f8cafe8f55d61f3cc99beced7f806a2bfd0d99c25ba
- Size of remote file:
- 4.88 GB
- SHA256:
- 02947859f8e2f8658defaac58b6f03a2e5acb461a8f8e90ab44f0e3ae915f84c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.