Text Classification
PEFT
Safetensors
Transformers
modality-routing
lora
mom
vllm-semantic-router
mixture-of-models
modernbert
Eval Results (legacy)
Instructions to use vllm-sr/mmbert32k-modality-router-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use vllm-sr/mmbert32k-modality-router-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-modality-router-lora") - Transformers
How to use vllm-sr/mmbert32k-modality-router-lora with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="vllm-sr/mmbert32k-modality-router-lora")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("vllm-sr/mmbert32k-modality-router-lora", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload label_mapping.json with huggingface_hub
Browse files- label_mapping.json +12 -0
label_mapping.json
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{
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"label_to_idx": {
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"AR": 0,
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"DIFFUSION": 1,
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"BOTH": 2
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},
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"idx_to_label": {
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"0": "AR",
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"1": "DIFFUSION",
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"2": "BOTH"
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}
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}
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