Image-Text-to-Text
GGUF
Safetensors
qwen3_5
llama.cpp
local-inference
quantized
qwen
qwen3.5
glm-5.1
glm-distillation
distillation
reasoning
chain-of-thought
long-cot
sft
lora
unsloth
instruction-tuned
conversational
text-generation
multilingual
math
stem
coding
research
experimental
Instructions to use Jackrong/Qwen3.5-9B-GLM5.1-Distill-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Local Apps Settings
- Unsloth Studio
How to use Jackrong/Qwen3.5-9B-GLM5.1-Distill-v1 with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Jackrong/Qwen3.5-9B-GLM5.1-Distill-v1 to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Jackrong/Qwen3.5-9B-GLM5.1-Distill-v1 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Jackrong/Qwen3.5-9B-GLM5.1-Distill-v1 to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="Jackrong/Qwen3.5-9B-GLM5.1-Distill-v1", max_seq_length=2048, )
- Xet hash:
- 66c1ba93cdffeaa2e7c274bf385ac79822179d2a4db03a1a6636cd1ef483d7ee
- Size of remote file:
- 5.37 GB
- SHA256:
- b54729b7bc05663c0e1a1b559ff1b80ae7a337c3a812bfdb587bab2df7a4938d
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