Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use LinusML/my_awesome_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LinusML/my_awesome_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="LinusML/my_awesome_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("LinusML/my_awesome_model") model = AutoModelForSequenceClassification.from_pretrained("LinusML/my_awesome_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from LinusML/my_awesome_model: direct link, hf CLI and curl.
- Browser
- Download file 5.2 kB
-
https://huggingface.co/LinusML/my_awesome_model/resolve/main/training_args.bin
- Command line
-
hf download hf://LinusML/my_awesome_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/LinusML/my_awesome_model/resolve/main/training_args.bin
5.2 kB
- Xet hash:
- da39485a20bae5f0445a9f5d7bdf7907cb8292c7f69f7e23ff801d581cb13fa7
- Size of remote file:
- 5.2 kB
- SHA256:
- 2b74566feb0ea0d82a9f8163183b23dde6b108d9d05739871f024ea5aebaa1c4
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