Text Classification
Transformers
Safetensors
English
qwen3_5
image-text-to-text
decision-model
classification
calibration
routing
guardrails
vision
multimodal
baseten
Instructions to use baselabs/mammoth-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use baselabs/mammoth-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="baselabs/mammoth-1")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("baselabs/mammoth-1") model = AutoModelForMultimodalLM.from_pretrained("baselabs/mammoth-1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Fix Mammoth’s CLI selecting the wrong engine
#3
by sheppo - opened
- serve.patch +19 -0
- test_cli_routing.py +68 -0
serve.patch
CHANGED
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@@ -783,3 +783,22 @@ index 4f6f7bd..ae428d9 100644
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try:
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opt.step()
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except torch.OutOfMemoryError:
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try:
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opt.step()
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except torch.OutOfMemoryError:
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diff --git a/qev/cli.py b/qev/cli.py
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--- a/qev/cli.py
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+++ b/qev/cli.py
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@@ -115,7 +115,14 @@
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if calib_path:
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logging.getLogger("qev.cli").info("calibration: %s", calib_path)
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config = json.loads((Path(model_path) / "config.json").read_text())
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- if args.multimodal or config.get("vision_config") is not None:
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+ from .readout import ReadoutConfig
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+
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+ # Only the patched text engine implements block-bidirectional attention.
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+ noncausal = ReadoutConfig.load(model_path).noncausal
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+ if args.multimodal and noncausal:
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+ raise SystemExit("Block-bidirectional attention is unsupported by the multimodal engine; "
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+ "omit --multimodal to serve text requests with DecisionEngine.")
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+ if args.multimodal or (config.get("vision_config") is not None and not noncausal):
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from .mm_engine import MMDecisionEngine
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engine = MMDecisionEngine(model_path, device=args.device, dtype=args.dtype, calibration=calib,
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test_cli_routing.py
ADDED
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@@ -0,0 +1,68 @@
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| 1 |
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"""CPU-only routing regression: python test_cli_routing.py /path/to/patched/OneJev."""
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import argparse
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import importlib.util
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import contextlib
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import json
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from pathlib import Path
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import sys
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import tempfile
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import types
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import unittest
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from unittest.mock import patch
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ROOT = Path(sys.argv.pop(1))
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class RoutingTest(unittest.TestCase):
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def route(self, config, readout=None, multimodal=False):
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# Import the actual readout module and execute the CLI; stub GPU/server boundaries.
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called = []
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def engine(kind):
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return lambda *a, **kw: called.append(kind) or object()
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mods = {}
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for name, attrs in {
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'uvicorn': {'run': lambda *a, **kw: None},
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'qev': {}, 'qev.calibrate': {'Calibration': object},
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'qev.engine': {'DecisionEngine': engine('text')},
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'qev.mm_engine': {'MMDecisionEngine': engine('multimodal'), 'local_model_dir': lambda x: x},
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'torch': {'nn': types.SimpleNamespace(Module=object)},
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'qev.prompt': {'MAX_SLOTS': 256},
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'qev.server': {'create_app': lambda *a, **kw: object()},
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}.items():
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mods[name] = types.ModuleType(name)
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mods[name].__dict__.update(attrs)
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with tempfile.TemporaryDirectory() as d, patch.dict(sys.modules, mods), patch('importlib.util.find_spec', return_value=object()):
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Path(d, 'config.json').write_text(json.dumps(config))
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if readout is not None:
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Path(d, 'readout.json').write_text(json.dumps(readout))
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spec = importlib.util.spec_from_file_location('qev.readout', ROOT / 'qev/readout.py')
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module = importlib.util.module_from_spec(spec)
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sys.modules['qev.readout'] = module
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spec.loader.exec_module(module)
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cli = {'__name__': 'qev.cli', '__package__': 'qev'}
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exec(compile((ROOT / 'qev/cli.py').read_text(), 'cli.py', 'exec'), cli)
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args = argparse.Namespace(model=d, calibration=None, multimodal=multimodal,
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gguf=None, llama_url=None, device='cpu', dtype='bfloat16', fork_mode='sequential',
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head_dtype='float32', media_root=None, no_gpu_preprocess=False, no_cuda_graphs=False,
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quantize=None, max_branch_tokens=16384, max_request_tokens=65536,
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name=None, host='127.0.0.1', port=8000)
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cli['cmd_serve'](args)
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return called
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def test_routes(self):
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layout = {'vision_config': {}, 'modeling_overrides': {'attention': {'full_attention': 'block_bidirectional'}}}
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for config, readout, explicit, expected in [
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(layout, None, False, 'text'), ({}, None, False, 'text'),
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({'vision_config': {}}, None, False, 'multimodal'),
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({'vision_config': {}}, None, True, 'multimodal'),
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({'vision_config': {}}, {'attention': 'noncausal'}, False, 'text'),
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({'vision_config': {}}, {'readout': 'head'}, False, 'multimodal'),
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]:
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with self.subTest(config=config, readout=readout, explicit=explicit):
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self.assertEqual(self.route(config, readout, explicit), [expected])
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with self.assertRaisesRegex(SystemExit, 'omit --multimodal'):
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self.route(layout, multimodal=True)
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with self.assertRaisesRegex(ValueError, 'unsupported full_attention'):
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self.route({'modeling_overrides': {'attention': {'full_attention': 'unknown'}}})
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if __name__ == '__main__':
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unittest.main()
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