space: load the Warden shipped in the repo (no boot download)
Browse files- .gitignore +3 -0
- space/app.py +26 -7
.gitignore
CHANGED
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@@ -28,3 +28,6 @@ finetune/_nemo_src/
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# OS / editor
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.DS_Store
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*.swp
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# OS / editor
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.DS_Store
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*.swp
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# the Space ships its model via hf upload, never via local git
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model/
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space/app.py
CHANGED
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@@ -57,7 +57,15 @@ STATIC = Path(__file__).parent / "static"
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# ------------------------------------------------------------ the Warden brain
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-
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INTERNAL_KEY = os.environ.get("SCRYPT_INTERNAL_KEY") or secrets.token_hex(16)
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tok = None
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@@ -127,16 +135,27 @@ if spaces is not None:
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tok = AutoTokenizer.from_pretrained(MODEL_ID, trust_remote_code=True)
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# 4-bit fits the `large` (48GB) slice and matches the Q4 GGUF the
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# local game ships — quality parity, not a downgrade.
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model = AutoModelForCausalLM.from_pretrained(
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MODEL_ID,
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trust_remote_code=True,
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quantization_config=BitsAndBytesConfig(
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load_in_4bit=True,
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bnb_4bit_quant_type="nf4",
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bnb_4bit_compute_dtype=torch.bfloat16,
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),
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device_map="cuda",
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)
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WARDEN_ERR = ""
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except Exception as err: # model is optional: the game survives without it
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# ------------------------------------------------------------ the Warden brain
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# Prefer the Warden shipped inside the Space repo (pre-quantized nf4, no
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# download at boot); fall back to the hub for self-hosters who clone without
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# the LFS weights.
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_SHIPPED = REPO_ROOT / "model"
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MODEL_ID = os.environ.get("WARDEN_MODEL") or (
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str(_SHIPPED)
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if (_SHIPPED / "config.json").exists()
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else "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16"
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)
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INTERNAL_KEY = os.environ.get("SCRYPT_INTERNAL_KEY") or secrets.token_hex(16)
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tok = None
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tok = AutoTokenizer.from_pretrained(MODEL_ID, trust_remote_code=True)
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# 4-bit fits the `large` (48GB) slice and matches the Q4 GGUF the
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# local game ships — quality parity, not a downgrade. The shipped
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# model/ dir is already nf4 (config carries quantization_config);
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# only quantize on the fly when loading raw BF16 from the hub.
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_cfg = Path(MODEL_ID) / "config.json"
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_already_quant = _cfg.exists() and "quantization_config" in _cfg.read_text()
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_quant_kwargs = (
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{}
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if _already_quant
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else {
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"quantization_config": BitsAndBytesConfig(
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load_in_4bit=True,
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bnb_4bit_quant_type="nf4",
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bnb_4bit_compute_dtype=torch.bfloat16,
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)
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}
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)
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model = AutoModelForCausalLM.from_pretrained(
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MODEL_ID,
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trust_remote_code=True,
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device_map="cuda",
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**_quant_kwargs,
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)
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WARDEN_ERR = ""
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except Exception as err: # model is optional: the game survives without it
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