File size: 2,134 Bytes
6d763d0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 | # Example: Build your own sovereign model with Summon
# pip install summon
# python examples/build_my_model.py
from summon import Summon
# ── Option A: Full pipeline ───────────────────────────────────
model = (
Summon.begin("AhmadMeta-v1") # name it whatever you want
.base("nemotron-mini-4b") # pick your base model
.corpus(layers=[ # point at your training data
"data/the_book.jsonl",
"data/enoch.jsonl",
"data/circle7.jsonl",
])
.constitutional([ # your model's principles
"truth",
"sovereignty",
"evidence",
"no_deception",
])
.license("sovereign-source-v1") # how you release it
.train(device="cuda", epochs=3) # train on your GPU
.push("my-org/AhmadMeta-v1") # push to HuggingFace
)
model.manifest()
# ── Option B: Corpus builder + model separately ───────────────
from summon import Summon
corpus = (
Summon.corpus()
.layer(0, "data/the_book.jsonl", name="genesis")
.layer(1, "data/enoch.jsonl", name="enochian")
.layer(2, "data/gospels.jsonl", name="hidden_gospels")
.layer(3, "data/circle7.jsonl", name="sovereign_lineage")
.layer(4, "data/book_of_dead.jsonl", name="world_wisdom")
.layer(5, "data/masters.jsonl", name="masters_of_art")
.seal()
)
model = (
Summon.begin("JessicaLM-v1")
.base("llama3-8b")
.corpus(corpus_obj=corpus)
.constitutional(["truth", "care", "sovereignty"])
.license("apache-2.0")
.train(device="cuda", epochs=5, batch_size=8)
.push("jessica-org/JessicaLM-v1")
)
# ── Option C: Dry run (validate config, no GPU needed) ────────
model = (
Summon.begin("TestModel-v1")
.base("phi3-mini")
.corpus(layers=["data/sample.jsonl"])
.constitutional(["truth"])
.train(dry_run=True) # just validates config
)
model.manifest()
|