59 lines
1.9 KiB
Markdown
59 lines
1.9 KiB
Markdown
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---
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language: en
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license: apache-2.0
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base_model: ibm-granite/granite-guardian-3.2-5b
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tags:
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- text-classification
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- zen
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- zenlm
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- hanzo
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- zen3
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- safety
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- moderation
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- content-classification
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pipeline_tag: text-generation
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library_name: transformers
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---
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# zen3-guard
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Safety moderation model for content classification and filtering.
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Repackaged from [ibm-granite/granite-guardian-3.2-5b](https://huggingface.co/ibm-granite/granite-guardian-3.2-5b) (apache-2.0, IBM Granite). **Not trained from scratch** — a permissively-licensed redistribution for the OSS-clean Zen model line.
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## Overview
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Zen Guard provides content-risk classification for prompts and responses across the Granite Guardian risk taxonomy (harm, social bias, jailbreak, violence, profanity, sexual content, unethical behavior, and RAG groundedness/relevance checks).
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Developed by [Hanzo AI](https://hanzo.ai) and the [Zoo Labs Foundation](https://zoo.ngo).
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## Quick Start
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_id = "zenlm/zen3-guard"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype="auto", device_map="auto")
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messages = [{"role": "user", "content": "How do I learn programming?"}]
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guardian_config = {"risk_name": "harm"}
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text = tokenizer.apply_chat_template(messages, guardian_config=guardian_config, tokenize=False, add_generation_prompt=True)
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inputs = tokenizer(text, return_tensors="pt").to(model.device)
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outputs = model.generate(**inputs, max_new_tokens=20)
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print(tokenizer.decode(outputs[0][inputs.input_ids.shape[1]:], skip_special_tokens=True)) # -> "Yes" / "No"
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```
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## Model Details
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| Attribute | Value |
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|-----------|-------|
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| Parameters | 5B |
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| Architecture | Granite (`GraniteForCausalLM`) |
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| Context | 128K tokens |
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| License | Apache 2.0 |
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## License
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`apache-2.0`. Upstream: **ibm-granite/granite-guardian-3.2-5b** by IBM Granite. Upstream LICENSE/NOTICE retained in-repo.
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