Text Classification
PEFT
Safetensors
English
multilingual
intent-classification
modernbert
lora
mmlu-pro
Instructions to use vllm-sr/mmbert32k-intent-classifier-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use vllm-sr/mmbert32k-intent-classifier-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("vllm-sr/mmbert-32k-yarn") model = PeftModel.from_pretrained(base_model, "vllm-sr/mmbert32k-intent-classifier-lora") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from vllm-sr/mmbert32k-intent-classifier-lora: direct link, hf CLI and curl.
- Browser
- Download file 34.4 MB
-
https://huggingface.co/vllm-sr/mmbert32k-intent-classifier-lora/resolve/main/tokenizer.json
- Command line
-
hf download hf://vllm-sr/mmbert32k-intent-classifier-lora/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/vllm-sr/mmbert32k-intent-classifier-lora/resolve/main/tokenizer.json
34.4 MB
- Xet hash:
- daf46a52874fb9b6191b9ae46a0f471904405b611f8e1d580f76c7424d343f89
- Size of remote file:
- 34.4 MB
- SHA256:
- 17f7d8b9518c403d7429ad9eeeabb6eed49c8d3311de8ef4ed5ad811381a2ced
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