Instructions to use moshew/MiniLM-L6-clinc-distilled with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use moshew/MiniLM-L6-clinc-distilled with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="moshew/MiniLM-L6-clinc-distilled")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("moshew/MiniLM-L6-clinc-distilled") model = AutoModelForSequenceClassification.from_pretrained("moshew/MiniLM-L6-clinc-distilled", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7e4a6a3741ed12c3b037f223947587ec82c533d9370b1b296e55569fedf6847b
- Size of remote file:
- 3.12 kB
- SHA256:
- bee2f932ecb41316c0f2c5e0787f86c09746f330486e43479cbf7d58f682d1ad
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