Comments (2)
You haven't quantized the ./models/13B/ggml-model-q4_0.bin.1
part of the model.
See the Readme - larger models produce several parts, each stored in a separate file with an integer suffix. At the moment, you need to quantize these parts individually
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Yep that was it, thanks!
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Related Issues (20)
- Feature Request: Support for fixie-ai/ultravox-v0_3
- Bug: OpenBLAS compile doesnโt work in Ubuntu 22.04 HOT 4
- Bug: GGML_SCHED_MAX_SPLITS must be increased to run BigLlama-3.1-681B-Instruct using GPU acceleration HOT 2
- Feature Request: please add falcon 7b mamba support HOT 1
- Bug: Unable to load phi3:3B(2.2GB) model on Apple M1 Pro HOT 4
- Feature Request: Avoid loading GPU layers into RAM before moving them to VRAM. This should allow the use of --no-mmap with models that do not fit in RAM but fit in RAM+VRAM. HOT 4
- Feature Request: support for nvidia/Llama-3.1-Minitron-4B-Width-Base HOT 8
- Bug: failed to load model with docker image HOT 7
- Vulkan adreno error
- Bug: Gemma2 adapter weights `lm_head` skipped on gguf conversion HOT 10
- Bug: MiniCPM-V-2.6 commit d565bb2fd5a2a58b9924a7a34e77a87c78c52137 causing crash in moondream HOT 15
- Bug: ImportError: libprotobuf-lite.so.25: cannot open shared object file: No such file or directory HOT 3
- Feature Request: Support dolphin-vision-72b HOT 1
- Bug: Flan UL2 uses wrong feed_forward_proj, also generates bad logits even if this is patched HOT 3
- Feature Request: Tensor Parallelism support HOT 1
- Bug: Inference on BF16 model does not use GPU acceleration. HOT 1
- Refactor: Add more typechecking to GGUFWriter.add_key_value
- Bug: Throughput (tokens/sec) does not scale with increasing batch sizes in Intel GPUs HOT 3
- Bug: Failed to convert minicpm-v2.5 HOT 3
- Bug: llama3.1 8B GGUF parallel inferring process leads to endless repeating results
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