Text Classification
Transformers
Safetensors
English
bert
MiniLM
MiniLM-L12
Intent-Matching
Intent
text-embeddings-inference
Instructions to use Kami0867/MiniLM-L12-Intent-Matching with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kami0867/MiniLM-L12-Intent-Matching with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Kami0867/MiniLM-L12-Intent-Matching")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Kami0867/MiniLM-L12-Intent-Matching") model = AutoModelForSequenceClassification.from_pretrained("Kami0867/MiniLM-L12-Intent-Matching", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Kami0867/MiniLM-L12-Intent-Matching: direct link, hf CLI and curl.
- Browser
- Download file 5.27 kB
-
https://huggingface.co/Kami0867/MiniLM-L12-Intent-Matching/resolve/main/training_args.bin
- Command line
-
hf download hf://Kami0867/MiniLM-L12-Intent-Matching/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Kami0867/MiniLM-L12-Intent-Matching/resolve/main/training_args.bin
5.27 kB
- Xet hash:
- 87c1f3f6e5d6ad629732f8252431df76fc1f2d6eea2ddcb413df97022ded7768
- Size of remote file:
- 5.27 kB
- SHA256:
- 7d25faac9a3fd130bed1c4de59f34804deed32c6c2783eed30045f4d7175f570
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