Instructions to use AXERA-TECH/InternVL2_5-1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AXERA-TECH/InternVL2_5-1B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="AXERA-TECH/InternVL2_5-1B")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("AXERA-TECH/InternVL2_5-1B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use AXERA-TECH/InternVL2_5-1B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "AXERA-TECH/InternVL2_5-1B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "AXERA-TECH/InternVL2_5-1B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/AXERA-TECH/InternVL2_5-1B
- SGLang
How to use AXERA-TECH/InternVL2_5-1B 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 "AXERA-TECH/InternVL2_5-1B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "AXERA-TECH/InternVL2_5-1B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "AXERA-TECH/InternVL2_5-1B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "AXERA-TECH/InternVL2_5-1B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use AXERA-TECH/InternVL2_5-1B with Docker Model Runner:
docker model run hf.co/AXERA-TECH/InternVL2_5-1B
Download main_448 from AXERA-TECH/InternVL2_5-1B: direct link, hf CLI and curl.
- Browser
- Download file 6.5 MB
-
https://huggingface.co/AXERA-TECH/InternVL2_5-1B/resolve/main/main_448
- Command line
-
hf download hf://AXERA-TECH/InternVL2_5-1B/main_448
-
curl -L -o main_448 https://huggingface.co/AXERA-TECH/InternVL2_5-1B/resolve/main/main_448
6.5 MB
- Xet hash:
- bd016a59c424dabed5917c0d332dbd818ab010698b4dd2bbf7f410e713014eae
- Size of remote file:
- 6.5 MB
- SHA256:
- 73cec3523aa04bfbfae4c0f5509a22f0fc40127fc7e20517ecaf28c085aa82ff
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