Intern-Decision-4B GGUF
GGUF conversion of internlm/Intern-Decision-4B, a multimodal structured-decision model fine-tuned from Qwen3.5-4B.
Files
| File | Purpose |
|---|---|
intern-decision-4b-fp16-fixed.gguf |
FP16 language model |
intern-decision-4b-q8_0-fixed.gguf |
Q8_0 language model |
mmproj-f16.gguf |
FP16 vision projector |
Choose one language model and pair it with mmproj-f16.gguf for multimodal inference.
The initial language-model conversions declared 33 transformer blocks while containing 32 tensor blocks. The uploaded FP16 and Q8_0 models correct the conversion metadata to block_count=32, nextn_predict_layers=0, and 32 recurrent-layer entries. Model tensors are unchanged. This correction is required by current llama.cpp builds.
llama.cpp
Use a current llama.cpp build with Qwen3.5 multimodal support:
llama-server \
--model intern-decision-4b-q8_0-fixed.gguf \
--mmproj mmproj-f16.gguf \
--host 127.0.0.1 \
--port 8767 \
--ctx-size 8192 \
--parallel 1 \
--gpu-layers all \
--flash-attn on
Intern-Decision is a candidate-scoring model rather than a general chat model. Follow the upstream model card's decision-schema prompt format, constrain each field to its allowed single-token answer symbols, and read the candidate probabilities. The upstream calibration temperature is 1.99241824; it was fitted on BF16 weights, so Q8_0 quantization can change calibration quality.
See the upstream model card for the request schema, inference protocol, benchmarks, and license details.