Instructions to use euclaise/Ferret-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use euclaise/Ferret-3B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="euclaise/Ferret-3B", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("euclaise/Ferret-3B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 45bb7363be10b78ba928cddb679b13ea554d34c42c6bfe365754d4136133ac55
- Size of remote file:
- 5.59 GB
- SHA256:
- 8111394cb153acca41aaebea73c4fbfafff7eb812e7c5148d810420af48470b9
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.