Zero-Shot Classification
PEFT
Safetensors
decision-model
classification
calibration
kev
system-one
lora
pointer-head
Instructions to use dhtocks/malkuth-4b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dhtocks/malkuth-4b with PEFT:
from peft import PeftModel from transformers import AutoModel base_model = AutoModel.from_pretrained("Qwen/Qwen3.5-4B-Base") model = PeftModel.from_pretrained(base_model, "dhtocks/malkuth-4b") - Notebooks
- Google Colab
- Kaggle
add pipeline_tag
Browse files
README.md
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base_model: Qwen/Qwen3.5-4B-Base
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base_model_relation: adapter
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library_name: peft
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license: cc-by-nc-4.0
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language: [en, ko, ja, zh, de, fr, es, hi, ar, th]
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tags: [decision-model, classification, calibration, kev, system-one, lora, pointer-head]
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base_model: Qwen/Qwen3.5-4B-Base
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base_model_relation: adapter
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library_name: peft
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pipeline_tag: zero-shot-classification
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license: cc-by-nc-4.0
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language: [en, ko, ja, zh, de, fr, es, hi, ar, th]
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tags: [decision-model, classification, calibration, kev, system-one, lora, pointer-head]
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