Image-Text-to-Text
Transformers
GGUF
Safetensors
vision
multimodal
text-generation-inference
unsloth
conversational
text-generation
qwen3_5
qwen3
qwen
27b
fine-tuned
instruction-tuned
reasoning
agent
agentic
tool-use
function-calling
code-generation
mtp
speculative-decoding
local-inference
Instructions to use Jackrong/Qwopus3.8-27B-Flash-V2-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jackrong/Qwopus3.8-27B-Flash-V2-GGUF with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="Jackrong/Qwopus3.8-27B-Flash-V2-GGUF") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Jackrong/Qwopus3.8-27B-Flash-V2-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Jackrong/Qwopus3.8-27B-Flash-V2-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Jackrong/Qwopus3.8-27B-Flash-V2-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Jackrong/Qwopus3.8-27B-Flash-V2-GGUF", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/Jackrong/Qwopus3.8-27B-Flash-V2-GGUF
- SGLang
How to use Jackrong/Qwopus3.8-27B-Flash-V2-GGUF with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "Jackrong/Qwopus3.8-27B-Flash-V2-GGUF" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Jackrong/Qwopus3.8-27B-Flash-V2-GGUF", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "Jackrong/Qwopus3.8-27B-Flash-V2-GGUF" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Jackrong/Qwopus3.8-27B-Flash-V2-GGUF", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }' - Unsloth Desktop
- Docker Model Runner
How to use Jackrong/Qwopus3.8-27B-Flash-V2-GGUF with Docker Model Runner:
docker model run hf.co/Jackrong/Qwopus3.8-27B-Flash-V2-GGUF
Download Qwopus3.8-27B-Flash-V2-MTP-Q5_K_S.gguf from Jackrong/Qwopus3.8-27B-Flash-V2-GGUF: direct link, hf CLI and curl.
- Browser
- Download file 19 GB
-
https://huggingface.co/Jackrong/Qwopus3.8-27B-Flash-V2-GGUF/resolve/main/Qwopus3.8-27B-Flash-V2-MTP-Q5_K_S.gguf
- Command line
-
hf download hf://Jackrong/Qwopus3.8-27B-Flash-V2-GGUF/Qwopus3.8-27B-Flash-V2-MTP-Q5_K_S.gguf
-
curl -L -o Qwopus3.8-27B-Flash-V2-MTP-Q5_K_S.gguf https://huggingface.co/Jackrong/Qwopus3.8-27B-Flash-V2-GGUF/resolve/main/Qwopus3.8-27B-Flash-V2-MTP-Q5_K_S.gguf
19 GB
- Xet hash:
- 6a4df5645046df5f20789686574cccd9239443a002e48183d9f8b01f92b074e1
- Size of remote file:
- 19 GB
- SHA256:
- adf3a7d028769557913a69b1dc47d29ff8497180fdfe94bb9b88b40124225fe3
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