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
Publish AdaptIQ-7B artifacts
Browse files
README.md
CHANGED
|
@@ -1,20 +1,78 @@
|
|
| 1 |
---
|
| 2 |
library_name: transformers
|
| 3 |
pipeline_tag: text-generation
|
|
|
|
| 4 |
tags:
|
| 5 |
- adaptiq
|
| 6 |
- 210-code-labs
|
| 7 |
- code
|
| 8 |
- agent
|
| 9 |
-
-
|
|
|
|
| 10 |
---
|
| 11 |
|
| 12 |
# AdaptIQ-7B
|
| 13 |
|
| 14 |
-
AdaptIQ
|
| 15 |
-
|
| 16 |
-
|
| 17 |
|
| 18 |
-
|
| 19 |
-
|
| 20 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
---
|
| 2 |
library_name: transformers
|
| 3 |
pipeline_tag: text-generation
|
| 4 |
+
license: apache-2.0
|
| 5 |
tags:
|
| 6 |
- adaptiq
|
| 7 |
- 210-code-labs
|
| 8 |
- code
|
| 9 |
- agent
|
| 10 |
+
- routed-experts
|
| 11 |
+
- openai-compatible
|
| 12 |
---
|
| 13 |
|
| 14 |
# AdaptIQ-7B
|
| 15 |
|
| 16 |
+
AdaptIQ is an open-weight, self-hosted routed-expert AI system from **210 Code Labs**.
|
| 17 |
+
This repository publishes the AdaptIQ model card, manifest, and deployment metadata for
|
| 18 |
+
`AdaptIQ-7B`.
|
| 19 |
|
| 20 |
+
## Architecture
|
| 21 |
+
|
| 22 |
+
AdaptIQ uses expert composition instead of unsafe direct weight blending across incompatible
|
| 23 |
+
architectures:
|
| 24 |
+
|
| 25 |
+
| Capability | Expert |
|
| 26 |
+
|---|---|
|
| 27 |
+
| Text / reasoning | `mistralai/Mistral-7B-Instruct-v0.3` |
|
| 28 |
+
| Code / debugging | `ibm-granite/granite-8b-code-instruct` |
|
| 29 |
+
| Image generation | `black-forest-labs/FLUX.1-schnell` |
|
| 30 |
+
|
| 31 |
+
Composition method: `routed_experts`. `alpha=0.5` is retained only for compatible linear-merge
|
| 32 |
+
experiments and is not used by the routed-expert release path.
|
| 33 |
+
|
| 34 |
+
## Capabilities
|
| 35 |
+
|
| 36 |
+
- General text chat
|
| 37 |
+
- Code generation and debugging
|
| 38 |
+
- Agent-oriented reasoning workflows
|
| 39 |
+
- Image generation through the routed image expert
|
| 40 |
+
- OpenAI-compatible hosted API on Modal
|
| 41 |
+
- MCP-ready tool schema scaffold
|
| 42 |
+
|
| 43 |
+
## Hosted API
|
| 44 |
+
|
| 45 |
+
Modal endpoint:
|
| 46 |
+
|
| 47 |
+
```text
|
| 48 |
+
https://codelabs--adaptiq-api-api.modal.run/v1
|
| 49 |
+
```
|
| 50 |
+
|
| 51 |
+
Model name:
|
| 52 |
+
|
| 53 |
+
```text
|
| 54 |
+
AdaptIQ-7B
|
| 55 |
+
```
|
| 56 |
+
|
| 57 |
+
Example:
|
| 58 |
+
|
| 59 |
+
```bash
|
| 60 |
+
curl https://codelabs--adaptiq-api-api.modal.run/v1/models \
|
| 61 |
+
-H "Authorization: Bearer $ADAPTIQ_API_KEY"
|
| 62 |
+
```
|
| 63 |
+
|
| 64 |
+
## Intended use
|
| 65 |
+
|
| 66 |
+
AdaptIQ is intended for software development, automation, research, education, and creative
|
| 67 |
+
self-hosted generation workflows.
|
| 68 |
+
|
| 69 |
+
## Limitations
|
| 70 |
+
|
| 71 |
+
This release is a routed expert system metadata release. It does not package all upstream expert
|
| 72 |
+
weights into a single checkpoint. Runtime deployments download/load the configured open-weight
|
| 73 |
+
experts according to the AdaptIQ manifest.
|
| 74 |
+
|
| 75 |
+
## License
|
| 76 |
+
|
| 77 |
+
The AdaptIQ release metadata is Apache-2.0. Respect the licenses and model cards of all upstream
|
| 78 |
+
experts before redistribution or commercial deployment.
|