Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
English
roberta
text-embeddings-inference
Instructions to use smeintadmin/image_intents with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use smeintadmin/image_intents with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="smeintadmin/image_intents")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("smeintadmin/image_intents") model = AutoModelForSequenceClassification.from_pretrained("smeintadmin/image_intents", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
3992336
1
Parent(s): 1ae8986
Upload 7 files
Browse files
checkpoint-500/config.json
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"position_embedding_type": "absolute",
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"torch_dtype": "float32",
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checkpoint-500/optimizer.pt
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checkpoint-500/pytorch_model.bin
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checkpoint-500/scheduler.pt
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checkpoint-500/trainer_state.json
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checkpoint-500/training_args.bin
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