Instructions to use Dcolinmorgan/distaster-mlx-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dcolinmorgan/distaster-mlx-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Dcolinmorgan/distaster-mlx-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Dcolinmorgan/distaster-mlx-model") model = AutoModelForSequenceClassification.from_pretrained("Dcolinmorgan/distaster-mlx-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 176e19bdb4879903c82808c249de63b9614bf74ed325f384bbf9b6a90e6c0fce
- Size of remote file:
- 4.86 kB
- SHA256:
- 6c5321858afcafb121be6c585853b5decaa1ec5094adf12c3fd1aedd2f574a5d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.