GUIDE teknik
Format serialisasioŋ model
Serialisasioŋ model mooy anam wi ñuy denc modelu masin buy jàng ci disk bi suko defee ñu mëna ko sarse ba noppi doxal ko ginaaw, ci beneen masin wala ci beneen làkk.
Déglul tegtal biiIA-nettali · ~2 min
Ci xët wii2 simili jàng
Résumé
Format bi nga tànn dina am njeexital ci yobbu gi, gaawaay bi, dayo fichier bi, ba ci kaaraange gi.
Plongeur bu xóot
After training, a model is just numbers (weights) plus a description of its architecture. Serialization writes that state into a file. Different ecosystems use different formats. Python pickle can execute arbitrary code when loading untrusted data. Many PyTorch checkpoints use pickle-based serialization, but torch.load security behavior is version-sensitive: PyTorch 2.6 and later default to weights_only=True when no pickle module is specified. Check the installed documentation and avoid disabling this protection for untrusted files. ONNX (Open Neural Network Exchange) is a framework-neutral format that lets a model trained in PyTorch run in another runtime or language. TensorFlow SavedModel is a directory format used for serving. Keras 3 saves to the native .keras format by default; its model.export API can produce a SavedModel for TensorFlow serving. Check the version-specific API. For large language models, safetensors has become popular because it stores only tensor data in a simple, fast, memory-mappable layout with no code execution, making it both safer and quicker to load. GGUF is widely used for running quantized LLMs efficiently on local hardware.
Doxal ci àdduna dëgg
Benn ekip dafay tàggat benn model ci PyTorch, yóbbu ko ci ONNX, ba noppi doxal ko ci biir benn aplikaasioŋu C# bu amul benn dependence ci Python.
Hugging Face dafay séddale diisaayu model yi ni ay safetensor suko defee jëfandikukat yi mëna leen yebbi te duñu am risku def kode bu baaxul.
Developpeur bi dafay yebbi benn fichier GGUF bu benn LLM buñ kwante ngir doxal ko ci CPU ordinatër portable.
Ab sarwiisu TensorFlow dafay yab ab répertoire SavedModel bu def graphe bi ak ay variable ngir joxe ay waxtaan jaaraleko ci ab API.
Ëlëgu formaa serialisasioŋ model
Xaarandil wéyal dajale formaa yu wóor te portabal. Safetensors mooy nekk default ngir séddoo poids model ci mbooloo ndax dafay dindi risku kode-execution bu pickle, te GGUF mooy de facto standard ngir LLM local inference ak quantization. ONNX mingi wéy di yaatu nekk pont bi diggante kaadar tàggat ak runtimes yu baax ci aparey yi, navigateurs yi ak accelerator yi. Ci gàttal, tendaas bi dafa taamu formaa yu amul benn làkk, budul yàq mémoire bi, te wóor ci jëmmal.
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Moytul
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Jéego yi ci topp
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Nattal sa bopp
Take the Model Serialization Formats quiz
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Luy formaa serialisasioŋ model?
Serialisasioŋ model mooy anam wi ñuy denc modelu masin buy jàng ci disk bi suko defee ñu mëna ko sarse ba noppi doxal ko ginaaw, ci beneen masin wala ci beneen làkk. Format bi nga tànn dina am njeexital ci yobbu gi, gaawaay bi, dayo fichier bi, ba ci kaaraange gi.
Lan moo waral ñuy jàppee formaa pickle bu Python ni risku kaaraange ci model yi?
Unpickling mën na doxal kode bu la neex, kon sooy yab fichier pickle bu wóorul mën na yàq sa sistem.
Lan mooy njariñu format ONNX?
ONNX formaa weccoo bu amul benn boor la, muy may portabilite ci runtime yi, làkk yi ak aparey yi.
Lan moo waral safetensors nekk lu siiw ci séddoo poids model?
Safetensors moytu kode-execution risku pickle ak charge ci gaaw jaaraleko ci memory mapping, muy gëna wóor te gaaw.
GGUF moo gëna méngoo ak ban jëfandikoo?
GGUF mooy formaa bi de facto ngir séddale ak doxal LLM yu bari ci gox bi te baax.
Lan la formaa weccoo bu melni ONNX di njëkka denc?
ONNX dafay jàpp graphe calcul model bi ak ay parametre ci benn schema buñ miin suko defee bépp runtime bu méngoo mëna ko def.
Weyal di jàng
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