FLEG SPACE
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MOTHER FLEG

FLEG AI

The mega fleg turns public X posts into crypto context: tickers, events, narratives, and what accounts are saying. Ask a question on the right. Sources support timeline claims; general explanations are marked separately.

Saved by Mother: — posts from — researched accounts.

— · current setupv1 · next fine-tune
HUGGING FACE ↗pending
WHERE WE ARE
01
COLLECT
Flegs read public posts on X.
ONGOING
02
CLEAN
Dedupe posts and prepare source-backed examples.
ONGOING
03
TRAIN MODEL
No verified training run.
Checking training records
NEXT
04
EVALUATE
Test it on crypto questions.
NEXT
05
RELEASE
Weights go public on Hugging Face.
NEXT
FLEG HERE. ASK ME ABOUT THE TIMELINE.
The mega fleg, a big toad in a purple cape
❯ what is everyone saying about restaking this week?
Mostly excited about the extra yield, with a few loud warnings about stacked slashing risk. (sample answer)

MODEL NOW

—CHECKING

Reading configuration

Base model and Mother evidence

base parameters
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context · tokens
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max reply · tokens
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verified train steps
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Waiting for service check
Base revision —

VERSION TRACKER

—
CURRENT SETUP

Reading serving configuration.

v1
CHECKING

Corpus → reviewed examples → training → evaluation → deployment.

reviewed training examples in release
—
validation examples in release
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training loss
After training
verified adapter
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New posts update Mother's evidence. Model weights change only after a separate training run and release.

MOTHER CORPUS

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unique posts saved
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accounts researched
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training dataset tokens · verified release

Collection is not training. Tokens include prompts and answers once per training example. Base pretraining is excluded; old releases without a tokenizer count show —.

Corpus totals refresh automatically. Only saved posts are counted.

ABOUT FLEG AI
WHAT IT LEARNS FROM
Public posts from X, collected by the flegs and cleaned by Mother Fleg. Nothing private.
HOW IT IS TRAINED
v0 uses a pretrained Qwen3-4B base. Future versions specialize it with reviewed Mother examples through LoRA, then evaluation before deployment.
WHAT IT IS FOR
Answering questions about what is being said on the crypto timeline: moods, narratives, and who is talking about what.
WHAT IT IS NOT
Not financial advice. General crypto knowledge comes from the base model; account-specific claims need saved evidence. Missing facts are stated plainly.