Why Does bitnet.cpp Throw an Error When I Try to Run Inference With a Model Downloaded From Hugging Face? #183
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I followed the instructions to download a BitNet model from Hugging Face (specifically BitNet-b1.58-2B-4T) using huggingface-cli, and placed it in the models/ directory. However, when I run run_inference.py with the -m flag pointing to the model path, I get an error saying the model file is missing or in an unsupported format. The directory contains several .gguf files. Am I missing a conversion step or is there a specific naming convention bitnet.cpp expects? |
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Replies: 1 comment
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This issue usually stems from not specifying the full path to the exact .gguf model file in your inference command. bitnet.cpp expects the -m argument to point directly to the .gguf model (e.g., models/BitNet-b1.58-2B-4T/ggml-model-i2_s.gguf), not just the model folder. If you're seeing multiple .gguf files, ensure you're selecting the one with the correct quantization type (i2_s, tl1, etc.) that matches your setup. Also, make sure the model was downloaded with the --local-dir flag and not just as a repo clone. If in doubt, rerun the setup using setup_env.py, which automatically prepares the model in the expected structure for inference. |
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This issue usually stems from not specifying the full path to the exact .gguf model file in your inference command. bitnet.cpp expects the -m argument to point directly to the .gguf model (e.g., models/BitNet-b1.58-2B-4T/ggml-model-i2_s.gguf), not just the model folder. If you're seeing multiple .gguf files, ensure you're selecting the one with the correct quantization type (i2_s, tl1, etc.) that matches your setup. Also, make sure the model was downloaded with the --local-dir flag and not just as a repo clone. If in doubt, rerun the setup using setup_env.py, which automatically prepares the model in the expected structure for inference.