1.9 KiB
1.9 KiB
language, license, base_model, tags, pipeline_tag, library_name
| language | license | base_model | tags | pipeline_tag | library_name | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| en | apache-2.0 | ibm-granite/granite-guardian-3.2-5b |
|
text-generation | transformers |
zen3-guard
Safety moderation model for content classification and filtering.
Repackaged from 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.
Overview
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).
Developed by Hanzo AI and the Zoo Labs Foundation.
Quick Start
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "zenlm/zen3-guard"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype="auto", device_map="auto")
messages = [{"role": "user", "content": "How do I learn programming?"}]
guardian_config = {"risk_name": "harm"}
text = tokenizer.apply_chat_template(messages, guardian_config=guardian_config, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(text, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=20)
print(tokenizer.decode(outputs[0][inputs.input_ids.shape[1]:], skip_special_tokens=True)) # -> "Yes" / "No"
Model Details
| Attribute | Value |
|---|---|
| Parameters | 5B |
| Architecture | Granite (GraniteForCausalLM) |
| Context | 128K tokens |
| License | Apache 2.0 |
License
apache-2.0. Upstream: ibm-granite/granite-guardian-3.2-5b by IBM Granite. Upstream LICENSE/NOTICE retained in-repo.