Image-Text-to-Text
Transformers
Safetensors
English
qwen3_5_text
text-generation
esper
esper-3.1
esper-3
valiant
valiant-labs
qwen
qwen-3.5
qwen-3.5-27b
27b
reasoning
code
code-instruct
python
javascript
dev-ops
jenkins
terraform
ansible
docker
kubernetes
helm
grafana
prometheus
shell
bash
azure
aws
gcp
cloud
scripting
powershell
problem-solving
architect
engineer
developer
creative
analytical
expert
rationality
conversational
chat
instruct
Instructions to use ValiantLabs/Qwen3.5-27B-Esper3.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ValiantLabs/Qwen3.5-27B-Esper3.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="ValiantLabs/Qwen3.5-27B-Esper3.1") 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 AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("ValiantLabs/Qwen3.5-27B-Esper3.1") model = AutoModelForCausalLM.from_pretrained("ValiantLabs/Qwen3.5-27B-Esper3.1") 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?"} ] }, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ValiantLabs/Qwen3.5-27B-Esper3.1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ValiantLabs/Qwen3.5-27B-Esper3.1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ValiantLabs/Qwen3.5-27B-Esper3.1", "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/ValiantLabs/Qwen3.5-27B-Esper3.1
- SGLang
How to use ValiantLabs/Qwen3.5-27B-Esper3.1 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 "ValiantLabs/Qwen3.5-27B-Esper3.1" \ --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": "ValiantLabs/Qwen3.5-27B-Esper3.1", "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 "ValiantLabs/Qwen3.5-27B-Esper3.1" \ --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": "ValiantLabs/Qwen3.5-27B-Esper3.1", "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" } } ] } ] }' - Docker Model Runner
How to use ValiantLabs/Qwen3.5-27B-Esper3.1 with Docker Model Runner:
docker model run hf.co/ValiantLabs/Qwen3.5-27B-Esper3.1
Upload folder using huggingface_hub
#1
by sequelbox - opened
No description provided.
This PR fixes the 'improperly merged weights' issue of the original upload. The model should now work as intended.
We'll continue to verify and fix any additional issues if found.
sequelbox changed pull request status to merged