Instructions to use 210Codelabs/AdaptIQ-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 210Codelabs/AdaptIQ-7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="210Codelabs/AdaptIQ-7B")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("210Codelabs/AdaptIQ-7B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use 210Codelabs/AdaptIQ-7B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "210Codelabs/AdaptIQ-7B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "210Codelabs/AdaptIQ-7B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/210Codelabs/AdaptIQ-7B
- SGLang
How to use 210Codelabs/AdaptIQ-7B 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 "210Codelabs/AdaptIQ-7B" \ --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": "210Codelabs/AdaptIQ-7B", "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 "210Codelabs/AdaptIQ-7B" \ --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": "210Codelabs/AdaptIQ-7B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use 210Codelabs/AdaptIQ-7B with Docker Model Runner:
docker model run hf.co/210Codelabs/AdaptIQ-7B
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Download README.md from 210Codelabs/AdaptIQ-7B: direct link, hf CLI and curl.
- Browser
- Download file 2 kB
-
https://huggingface.co/210Codelabs/AdaptIQ-7B/resolve/main/README.md
- Command line
-
hf download hf://210Codelabs/AdaptIQ-7B/README.md
-
curl -L -o README.md https://huggingface.co/210Codelabs/AdaptIQ-7B/resolve/main/README.md
2 kB
| library_name: transformers | |
| pipeline_tag: text-generation | |
| license: apache-2.0 | |
| tags: | |
| - adaptiq | |
| - 210-code-labs | |
| - code | |
| - agent | |
| - routed-experts | |
| - openai-compatible | |
| # AdaptIQ-7B | |
| AdaptIQ is an open-weight, self-hosted routed-expert AI system from **210 Code Labs**. | |
| This repository publishes the AdaptIQ model card, manifest, and deployment metadata for | |
| `AdaptIQ-7B`. | |
| ## Architecture | |
| AdaptIQ uses expert composition instead of unsafe direct weight blending across incompatible | |
| architectures: | |
| | Capability | Expert | | |
| |---|---| | |
| | Text / reasoning | `mistralai/Mistral-7B-Instruct-v0.3` | | |
| | Code / debugging | `ibm-granite/granite-8b-code-instruct` | | |
| | Image generation | `stabilityai/sd-turbo` | | |
| Composition method: `routed_experts`. `alpha=0.5` is retained only for compatible linear-merge | |
| experiments and is not used by the routed-expert release path. | |
| ## Capabilities | |
| - General text chat | |
| - Code generation and debugging | |
| - Agent-oriented reasoning workflows | |
| - Image generation through the routed image expert | |
| - OpenAI-compatible hosted API on Modal | |
| - MCP-ready tool schema scaffold | |
| ## Hosted API | |
| Modal endpoint: | |
| ```text | |
| https://codelabs--adaptiq-api-api.modal.run/v1 | |
| ``` | |
| Model name: | |
| ```text | |
| AdaptIQ-7B | |
| ``` | |
| Example: | |
| ```bash | |
| curl https://codelabs--adaptiq-api-api.modal.run/v1/models \ | |
| -H "Authorization: Bearer $ADAPTIQ_API_KEY" | |
| ``` | |
| ## Intended use | |
| AdaptIQ is intended for software development, automation, research, education, and creative | |
| self-hosted generation workflows. | |
| ## Limitations | |
| This release is a routed expert system metadata release. It does not package all upstream expert | |
| weights into a single checkpoint. Runtime deployments download/load the configured open-weight | |
| experts according to the AdaptIQ manifest. | |
| ## License | |
| The AdaptIQ release metadata is Apache-2.0. Respect the licenses and model cards of all upstream | |
| experts before redistribution or commercial deployment. | |