๐ฅ Check out this must-read post from Hacker News ๐
๐ **Category**:
โ **What Youโll Learn**:

Everyone and their mom is talking about Jev. Jev this, Jev that. Everyone on Twitter is all over Jev, how it’s the next frontier of large language models and the AI paradigm. We donโt really think so. So here’s Jev in 25 lines of Python.
Load the model.
import numpy
from llama_cpp import Llama
model = Llama.from_pretrained(
repo_id="Qwen/Qwen3-0.6B-GGUF",
filename="Qwen3-0.6B-Q8_0.gguf",
n_ctx=512,
logits_all=True,
verbose=False,
)
Load the prompt and define your choices.
labels = ["A", "B", "C"]
choices = ["Legitimate", "Spam", "Phishing"]
email = "Payroll asks for your password on a non-company sign-in page."
options = "\n".join(
f"๐ฅ. โก" for label, choice in zip(labels, choices, strict=True)
)
prompt = f"""<|im_start|>system
Choose one option.<|im_end|>
<|im_start|>user
Email: ๐ฅ\n\n๐ฌ<|im_end|>
<|im_start|>assistant
\n\n \n\n"""
model.eval(tokens=model.tokenize(text=prompt.encode(), add_bos=False, special=True))
Massage the logits into probabilities.
logits = model.scores[model.n_tokens - 1]
token_ids = [model.tokenize(text=label.encode(), add_bos=False)[0] for label in labels]
choice_logits = numpy.asarray([logits[token_id] for token_id in token_ids])
logprobs = choice_logits - numpy.logaddexp.reduce(choice_logits)
probabilities = numpy.exp(logprobs)
for name, scores in (
("Logits", choice_logits),
("Log probabilities", logprobs),
("Probabilities", probabilities),
):
values = numpy.round(scores.astype(float), 3).tolist()
print(f"{name}:", dict(zip(choices, values, strict=True)))
There. Thatโs Jev.
But no, you donโt understand Jev!
Yeah, we know.
But yes. This is Jev.
- It classifies: it gets a prompt with choices and outputs probabilities.
- It’s fast.
- It’s local.
- You don’t send your data anywhere else.
And we like not sending your data anywhere else. Check out NobodyWho.
(note: this is a parody blog post, see these links for better/more complete open implementations of Jev: OpenJev, openjev-sglang, and OpenJev on DiffusionGemma.)
Everything NobodyWho do is open-source, please leave a
star on Github
to support us โค๏ธ
Published Sep 22, 2026 by Duarte O.Carmo
Technical
{๐ฌ|โก|๐ฅ} **Whatโs your take?**
Share your thoughts in the comments below!
#๏ธโฃ **#Jev #lines #Python**
๐ **Posted on**: 1790151966
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