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: 296 Bytes
015c04d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | {
"bos_token": {
"content": "<|begin_of_text|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false
},
"eos_token": {
"content": "<|eot_id|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false
}
}
|