Image-Text-to-Text
Transformers
Safetensors
multilingual
internvl_chat
feature-extraction
internvl
custom_code
conversational
compressed-tensors
Instructions to use cyankiwi/InternVL3_5-8B-AWQ-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cyankiwi/InternVL3_5-8B-AWQ-4bit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="cyankiwi/InternVL3_5-8B-AWQ-4bit", trust_remote_code=True) 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("cyankiwi/InternVL3_5-8B-AWQ-4bit", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use cyankiwi/InternVL3_5-8B-AWQ-4bit with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "cyankiwi/InternVL3_5-8B-AWQ-4bit" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "cyankiwi/InternVL3_5-8B-AWQ-4bit", "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/cyankiwi/InternVL3_5-8B-AWQ-4bit
- SGLang
How to use cyankiwi/InternVL3_5-8B-AWQ-4bit 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 "cyankiwi/InternVL3_5-8B-AWQ-4bit" \ --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": "cyankiwi/InternVL3_5-8B-AWQ-4bit", "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 "cyankiwi/InternVL3_5-8B-AWQ-4bit" \ --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": "cyankiwi/InternVL3_5-8B-AWQ-4bit", "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 cyankiwi/InternVL3_5-8B-AWQ-4bit with Docker Model Runner:
docker model run hf.co/cyankiwi/InternVL3_5-8B-AWQ-4bit
Download recipe.yaml from cyankiwi/InternVL3_5-8B-AWQ-4bit: direct link, hf CLI and curl.
- Browser
- Download file 1.15 kB
-
https://huggingface.co/cyankiwi/InternVL3_5-8B-AWQ-4bit/resolve/main/recipe.yaml
- Command line
-
hf download hf://cyankiwi/InternVL3_5-8B-AWQ-4bit/recipe.yaml
-
curl -L -o recipe.yaml https://huggingface.co/cyankiwi/InternVL3_5-8B-AWQ-4bit/resolve/main/recipe.yaml
1.15 kB
| quant_stage: | |
| quant_modifiers: | |
| AWQModifier: | |
| config_groups: | |
| group_0: | |
| targets: [Linear] | |
| weights: | |
| num_bits: 4 | |
| type: int | |
| symmetric: true | |
| group_size: 32 | |
| strategy: group | |
| block_structure: null | |
| dynamic: false | |
| actorder: null | |
| observer: mse | |
| observer_kwargs: {} | |
| input_activations: null | |
| output_activations: null | |
| format: null | |
| targets: [Linear] | |
| ignore: [language_model.lm_head, language_model.model.embed_tokens, 're:.*input_layernorm', | |
| 're:.*post_attention_layernorm', language_model.model.norm, 're:vision_model.*', 're:mlp1.*'] | |
| mappings: | |
| - smooth_layer: re:.*input_layernorm$ | |
| balance_layers: ['re:.*q_proj$', 're:.*k_proj$', 're:.*v_proj$'] | |
| - smooth_layer: re:.*v_proj$ | |
| balance_layers: ['re:.*o_proj$'] | |
| - smooth_layer: re:.*post_attention_layernorm$ | |
| balance_layers: ['re:.*gate_proj$', 're:.*up_proj$'] | |
| - smooth_layer: re:.*up_proj$ | |
| balance_layers: ['re:.*down_proj$'] | |
| duo_scaling: true | |