Text Classification
Transformers
TensorBoard
Safetensors
bert
HHD
10_class
multi_labels
Generated from Trainer
text-embeddings-inference
Instructions to use eyeon/model_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eyeon/model_output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="eyeon/model_output")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("eyeon/model_output") model = AutoModelForSequenceClassification.from_pretrained("eyeon/model_output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from eyeon/model_output: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/eyeon/model_output/resolve/main/training_args.bin
- Command line
-
hf download hf://eyeon/model_output/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/eyeon/model_output/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- 2d94b477edb70e3f12c3f57a4921dbb20e14c27b9ce8206555f4f6f796aa5e58
- Size of remote file:
- 5.3 kB
- SHA256:
- 8533eb6df6cb4072a8ae116f05b4f97177f0803bc1b4904fd892c219cf74ef84
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