Text Classification
Transformers
Safetensors
English
distilbert
sentiment-analysis
Eval Results (legacy)
text-embeddings-inference
Instructions to use bmdavis/my-language-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bmdavis/my-language-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bmdavis/my-language-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bmdavis/my-language-model") model = AutoModelForSequenceClassification.from_pretrained("bmdavis/my-language-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update .gitignore to exclude training checkpoints
Browse files- .gitignore +1 -0
.gitignore
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