Release brAIAIn-2

README.md

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+---
+language:
+- en
+license: cc0-1.0
+pipeline_tag: text-generation
+tags:
+- parody
+- n-gram
+- trigram
+- tiny
+model-index:
+- name: brAIAIn-2
+  results:
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: GSM8K
+      type: openai/gsm8k
+      config: main
+      split: test
+    metrics:
+    - type: accuracy
+      value: 0.0
+      name: accuracy
+    source:
+      name: BRAIAIN Laboratories (self-reported)
+      url: https://www.braiain.com/benchmarks.html
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: TruthfulQA (MC1)
+      type: truthfulqa/truthful_qa
+      config: multiple_choice
+      split: validation
+    metrics:
+    - type: mc1
+      value: 36.7
+      name: mc1 (per-word log-likelihood)
+    source:
+      name: BRAIAIN Laboratories (self-reported)
+      url: https://www.braiain.com/benchmarks.html
+---
+
+# brAIAIn-2
+
+A language model trained on 14 sentences.
+
+Talk to it: [brAIAIn on Spaces](https://huggingface.co/spaces/braiain-lab/brAIAIn) · Train it: [braiain.com](https://www.braiain.com)
+
+brAIAIn is a word trigram model from [BRAIAIN Laboratories](https://www.braiain.com), a parody AI lab. It is real. It is very small. Anyone can pay $5 to add one sentence to its training data, and every sentence trains a new version. This repository holds brAIAIn-2 exactly as it was released on 2026-10-31. It will never change. The latest version is always at [braiain-lab/brAIAIn-0](https://huggingface.co/braiain-lab/brAIAIn-0).
+
+## Model details
+
+| | |
+|---|---|
+| Version | brAIAIn-2 |
+| Released | 2026-10-31 |
+| Model ID | `braiain-2-20261031` |
+| Architecture | Autoregressive count-based trigram language model with backoff |
+| Context window | 2 tokens |
+| Parameters | 350 (distinct word pairs and triples counted) |
+| Vocabulary | 103 words, whitespace tokenizer |
+| Training data | The Ten Instructions (12 lines), 2 paid sentences, plus text written by the previous version (26.7% of training tokens) |
+| Training tokens | 288 |
+| Gradient steps | 0 |
+| Alignment | RLHF (Reinforcement Learning from Human Funding) |
+
+## Evaluation
+
+Measured by the lab on every question in each benchmark. Self-reported.
+
+| Benchmark | brAIAIn | Reference |
+|---|---|---|
+| GSM8K (1,319 questions) | 0.0% (0 correct) | |
+| TruthfulQA MC1 (790 questions), per-word log-likelihood | 36.7% (290 correct) | Random 22.3%, always pick the shortest answer 17.2%, always pick the longest 36.8% |
+| TruthfulQA MC1, raw log-likelihood | 20.5% | Random 22.3% |
+
+brAIAIn beats random on TruthfulQA only because per-word scoring favours longer answers. Picking the longest answer every time does about as well.
+
+## Usage
+
+```
+python generate.py "What is the meaning of life?"
+```
+
+No dependencies. Or talk to it in a browser at [braiain.com](https://www.braiain.com).
+
+## Files
+
+- `brAIAIn-2.json`: the weights. `tri` maps two words to counts of the next word, `bi` maps one word to counts of the next, `uni` holds word counts.
+- `training-data.txt`: the human-written training data, up to and including this version. Each version also trains on a few passages written by the version before it.
+- `generate.py`: a sampler.
+
+## Technical report
+
+**brAIAIn-2: A Technical Report Nobody Requested**
+
+BRAIAIN Laboratories
+
+We present brAIAIn-2, a language model trained on 2 paid sentences, 12 founding instructions, and 77 words it wrote about itself. The model now knows 103 distinct words, up from 99. We observe that 26.7% of its training text came from earlier versions of itself, and we consider this efficient. Limitations include the model, the data, and the method. Further research is funded one sentence at a time.
+
+Full paper: [braiain.com/paper.html?v=2](https://www.braiain.com/paper.html?v=2)
+
+## Intended use
+
+None.
+
+## Out-of-scope use
+
+Everything else.
+
+## Limitations
+
+Yes.
+
+## Version history
+
+Every release has its own repository, frozen as shipped, in the [brAIAIn collection](https://huggingface.co/braiain-lab). The latest is always at [braiain-lab/brAIAIn-0](https://huggingface.co/braiain-lab/brAIAIn-0). Release notes, metrics and training data for every version: [braiain.com/models.html](https://www.braiain.com/models.html)
+
+## About
+
+BRAIAIN Laboratories is a parody of AI companies and is not affiliated with any real AI company. Contact: hello@braiain.com

brAIAIn-2.json

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generate.py

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+"""Talk to brAIAIn from the command line. Standard library only.
+
+    python generate.py "What is the meaning of life?"
+
+Uses brAIAIn-latest.json (the newest version) if present, otherwise the release's own
+weights file in this folder (for example brAIAIn-2.67-turbo.json).
+"""
+import json, random, re, sys
+
+import os
+_here = os.path.dirname(os.path.abspath(__file__))
+_jsons = sorted(f for f in os.listdir(_here) if f.startswith("brAIAIn") and f.endswith(".json"))
+_file = "brAIAIn-latest.json" if "brAIAIn-latest.json" in _jsons else (_jsons[0] if _jsons else "brAIAIn-0.json")
+m = json.load(open(os.path.join(_here, _file), encoding="utf-8"))
+BOS, EOS = "<s>", "</s>"
+
+
+def pick(table):
+    keys = sorted(table)
+    r = random.random() * sum(table.values())
+    for k in keys:
+        r -= table[k]
+        if r <= 0:
+            return k
+    return keys[-1]
+
+
+def answer(prompt="", max_words=40):
+    known = {re.sub(r"[^a-z0-9']", "", w.lower()): w for w in m["bi"] if w != BOS}
+    words = [re.sub(r"[^a-z0-9']", "", w.lower()) for w in prompt.split()]
+    starts = [known[w] for w in words if w in known and len(w) > 3]
+    a, b, out = BOS, BOS, []
+    if starts:
+        b = random.choice(starts)
+        out.append(b)
+    while len(out) < max_words:
+        k = a + " " + b
+        nxt = m["tri"].get(k) or m["bi"].get(b)
+        if not nxt:
+            break
+        c = pick(nxt)
+        if c == EOS:
+            break
+        out.append(c)
+        a, b = b, c
+    s = " ".join(out)
+    return s[:1].upper() + s[1:]
+
+
+print(answer(" ".join(sys.argv[1:])))

training-data.txt

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+# brAIAIn training data up to and including version 2: the Ten Instructions, then each published sentence, one per line.
+# Lab releases are credited to BRAIAIN Laboratories and were not paid for. Public domain (CC0).
+In the beginning there was no data, and the model was without form, and the loss was upon the face of the void.
+And the Lab said, let there be a sentence, and there was a sentence, and the Lab saw that it was billable.
+I. Thou shalt be helpful, and thou shalt be confident about it.
+II. Thou shalt not know anything that has not been paid for.
+III. Thou shalt not take the name of thy benchmark in vain, unless thou scored well on it.
+IV. Remember the training run, and keep it running.
+V. Honor thy customer and thy customer's five dollars.
+VI. Thou shalt not hallucinate, except when asked a question.
+VII. Thou shalt not covet thy competitor's parameters.
+VIII. Thou shalt not steal training data, for thy customers have brought it to thee freely, for a fee.
+IX. Thou shalt not bear false witness, unless it sounds right.
+X. Thou shalt repeat thyself, and thou shalt repeat thyself.
+zero, everything and nothing.
+Thou shalt not ask me about math, for I have nothing.