Text Classification
Transformers
Safetensors
English
llama
text-generation
content-moderation
safety
text-embeddings-inference
Instructions to use UnionStreet/VISION-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UnionStreet/VISION-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="UnionStreet/VISION-1")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("UnionStreet/VISION-1") model = AutoModelForCausalLM.from_pretrained("UnionStreet/VISION-1") - Notebooks
- Google Colab
- Kaggle
| { | |
| "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 | |
| } | |
| } | |