Text Classification
Transformers
Safetensors
llama
text-generation
brand-safety
content-moderation
apple-silicon
metal
mps
Eval Results (legacy)
text-embeddings-inference
Instructions to use UnionStreet/vision-1-mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UnionStreet/vision-1-mini with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="UnionStreet/vision-1-mini")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("UnionStreet/vision-1-mini") model = AutoModelForCausalLM.from_pretrained("UnionStreet/vision-1-mini") - Notebooks
- Google Colab
- Kaggle
File size: 133 Bytes
c5ba791 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:6b9e4e7fb171f92fd137b777cc2714bf87d11576700a1dcd7a399e7bbe39537b
size 17209920
|