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
Upload generation_config.json with huggingface_hub
Browse files- generation_config.json +13 -0
generation_config.json
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{
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"bos_token_id": 128000,
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"do_sample": true,
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"eos_token_id": [
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128001,
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],
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"temperature": 0.6,
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"top_p": 0.9,
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"transformers_version": "4.48.0",
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"use_cache": false
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}
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