Text Generation
PEFT
Safetensors
English
Hindi
scam-detection
elder-fraud
gpt-oss
lora
qlora
unsloth
dgx-spark
conversational
Instructions to use Solomonwilsonr/kinshield-20b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Solomonwilsonr/kinshield-20b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gpt-oss-20b-unsloth-bnb-4bit") model = PeftModel.from_pretrained(base_model, "Solomonwilsonr/kinshield-20b") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Rename to KinShield-20b
Browse files
README.md
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tags: [scam-detection, elder-fraud, gpt-oss, lora, qlora, unsloth, dgx-spark]
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---
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# KinShield gpt-oss-20b
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A QLoRA adapter for OpenAI's **gpt-oss-20b** that turns it into [KinShield](https://zx9d4nrkni.execute-api.us-east-1.amazonaws.com/)'s phone-call evidence detector. KinShield is an entry in the AWS "Zero to Shipped" hackathon. The model reads a call transcript and returns strict JSON with:
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- a risk level (LOW / MEDIUM / HIGH) and a score
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```python
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from unsloth import FastLanguageModel
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model, tok = FastLanguageModel.from_pretrained("Solomonwilsonr/kinshield-
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max_seq_length=3072, load_in_4bit=True)
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FastLanguageModel.for_inference(model)
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SYSTEM = open("system_prompt.txt").read() # KinShield detector prompt, included in this repo
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tags: [scam-detection, elder-fraud, gpt-oss, lora, qlora, unsloth, dgx-spark]
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---
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# KinShield-20b: a QLoRA fine-tune of gpt-oss-20b
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A QLoRA adapter for OpenAI's **gpt-oss-20b** that turns it into [KinShield](https://zx9d4nrkni.execute-api.us-east-1.amazonaws.com/)'s phone-call evidence detector. KinShield is an entry in the AWS "Zero to Shipped" hackathon. The model reads a call transcript and returns strict JSON with:
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- a risk level (LOW / MEDIUM / HIGH) and a score
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```python
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from unsloth import FastLanguageModel
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model, tok = FastLanguageModel.from_pretrained("Solomonwilsonr/kinshield-20b",
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max_seq_length=3072, load_in_4bit=True)
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FastLanguageModel.for_inference(model)
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SYSTEM = open("system_prompt.txt").read() # KinShield detector prompt, included in this repo
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