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 +1 -1
- ROUTED_EXPERTS.txt +1 -1
- adaptiq_manifest.json +3 -3
README.md
CHANGED
|
@@ -26,7 +26,7 @@ architectures:
|
|
| 26 |
|---|---|
|
| 27 |
| Text / reasoning | `mistralai/Mistral-7B-Instruct-v0.3` |
|
| 28 |
| Code / debugging | `ibm-granite/granite-8b-code-instruct` |
|
| 29 |
-
| Image generation | `
|
| 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.
|
|
|
|
| 26 |
|---|---|
|
| 27 |
| Text / reasoning | `mistralai/Mistral-7B-Instruct-v0.3` |
|
| 28 |
| Code / debugging | `ibm-granite/granite-8b-code-instruct` |
|
| 29 |
+
| Image generation | `stabilityai/sd-turbo` |
|
| 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.
|
ROUTED_EXPERTS.txt
CHANGED
|
@@ -1,4 +1,4 @@
|
|
| 1 |
AdaptIQ uses routed expert composition for this variant.
|
| 2 |
text=mistralai/Mistral-7B-Instruct-v0.3
|
| 3 |
code=ibm-granite/granite-8b-code-instruct
|
| 4 |
-
image=
|
|
|
|
| 1 |
AdaptIQ uses routed expert composition for this variant.
|
| 2 |
text=mistralai/Mistral-7B-Instruct-v0.3
|
| 3 |
code=ibm-granite/granite-8b-code-instruct
|
| 4 |
+
image=stabilityai/sd-turbo
|
adaptiq_manifest.json
CHANGED
|
@@ -8,7 +8,7 @@
|
|
| 8 |
"mistralai/Mistral-7B-Instruct-v0.3",
|
| 9 |
"ibm-granite/granite-8b-code-instruct"
|
| 10 |
],
|
| 11 |
-
"image_expert": "
|
| 12 |
"composition": {
|
| 13 |
"method": "routed_experts",
|
| 14 |
"alpha": 0.5,
|
|
@@ -26,9 +26,9 @@
|
|
| 26 |
"license": "apache-2.0"
|
| 27 |
},
|
| 28 |
"image": {
|
| 29 |
-
"repo": "
|
| 30 |
"revision": "main",
|
| 31 |
-
"license": "
|
| 32 |
}
|
| 33 |
},
|
| 34 |
"brand": "AdaptIQ",
|
|
|
|
| 8 |
"mistralai/Mistral-7B-Instruct-v0.3",
|
| 9 |
"ibm-granite/granite-8b-code-instruct"
|
| 10 |
],
|
| 11 |
+
"image_expert": "stabilityai/sd-turbo",
|
| 12 |
"composition": {
|
| 13 |
"method": "routed_experts",
|
| 14 |
"alpha": 0.5,
|
|
|
|
| 26 |
"license": "apache-2.0"
|
| 27 |
},
|
| 28 |
"image": {
|
| 29 |
+
"repo": "stabilityai/sd-turbo",
|
| 30 |
"revision": "main",
|
| 31 |
+
"license": "stability-ai-community"
|
| 32 |
}
|
| 33 |
},
|
| 34 |
"brand": "AdaptIQ",
|