Instructions to use inclusionAI/Ling-3.0-flash-VL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Inference
- HuggingChat
- Notebooks
- Google Colab
- Kaggle
Trim SGLang launch command to the verified minimal recipe
Browse filesTrim the SGLang launch command to the verified minimal recipe.
All removed flags were verified as unnecessary on the current `lmsysorg/sglang:dev-Ling-3.0-flash-VL` image: serving smoke plus full MMMU-Pro / GSM8K / bench_serving were measured without them. The MXFP4 MoE backend and the ling3 parsers are auto-selected; `--mem-fraction-static` uses the engine default with no measured perf/accuracy impact.
See the cookbook for the per-hardware verified matrix: https://docs.sglang.io/cookbook/autoregressive/InclusionAI/Ling-3.0-flash-VL
README.md
CHANGED
|
@@ -70,7 +70,6 @@ docker run --rm --gpus all --ipc=host --shm-size 32g \
|
|
| 70 |
--tp 4 \
|
| 71 |
--context-length 262144 \
|
| 72 |
--json-model-override-args '{"rope_scaling":{"rope_type":"yarn","factor":2.0,"rope_theta":6000000,"partial_rotary_factor":0.5,"original_max_position_embeddings":131072}}' \
|
| 73 |
-
--mem-fraction-static 0.85 \
|
| 74 |
--trust-remote-code \
|
| 75 |
--reasoning-parser auto \
|
| 76 |
--tool-call-parser auto \
|
|
|
|
| 70 |
--tp 4 \
|
| 71 |
--context-length 262144 \
|
| 72 |
--json-model-override-args '{"rope_scaling":{"rope_type":"yarn","factor":2.0,"rope_theta":6000000,"partial_rotary_factor":0.5,"original_max_position_embeddings":131072}}' \
|
|
|
|
| 73 |
--trust-remote-code \
|
| 74 |
--reasoning-parser auto \
|
| 75 |
--tool-call-parser auto \
|