Instructions to use arcadia-impact/scimt-dispatch-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use arcadia-impact/scimt-dispatch-models with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="arcadia-impact/scimt-dispatch-models")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("arcadia-impact/scimt-dispatch-models", device_map="auto")

PEFT
How to use arcadia-impact/scimt-dispatch-models with PEFT:
```
Task type is invalid.
```
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use arcadia-impact/scimt-dispatch-models with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "arcadia-impact/scimt-dispatch-models"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "arcadia-impact/scimt-dispatch-models",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/arcadia-impact/scimt-dispatch-models

SGLang

How to use arcadia-impact/scimt-dispatch-models 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 "arcadia-impact/scimt-dispatch-models" \
    --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": "arcadia-impact/scimt-dispatch-models",
		"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 "arcadia-impact/scimt-dispatch-models" \
        --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": "arcadia-impact/scimt-dispatch-models",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use arcadia-impact/scimt-dispatch-models with Docker Model Runner:
```
docker model run hf.co/arcadia-impact/scimt-dispatch-models
```

sidbaines commited on 11 days ago

Commit

ca20892

verified ·

1 Parent(s): 813af99

dispatch_lora_grafting_v1: grafting_v1/control/COMPLETE.json

Browse files

Files changed (1) hide show

grafting_v1/control/COMPLETE.json +47 -0

grafting_v1/control/COMPLETE.json ADDED Viewed

	@@ -0,0 +1,47 @@

+{
+  "schema_version": "dispatch_lora_grafting_arm_complete_v1",
+  "status": "complete",
+  "version": "dispatch_lora_grafting_v1",
+  "run_id": "20260819T132410Z",
+  "arm": "control",
+  "completed_at": "2026-08-19T15:02:43+00:00",
+  "publications": {
+    "aft_adapter": {
+      "repo": "arcadia-impact/scimt-dispatch-models",
+      "repo_type": "model",
+      "revision": "1020aa8919c7f7084b401f4ccebbd10be749a13f",
+      "prefix": "grafting_v1/control/aft_adapter",
+      "files": 4,
+      "sizes_verified": true,
+      "lfs_sha256_verified": true,
+      "last_retry_error": null
+    },
+    "reconstruction": {
+      "revision": "813af99b51185ac3d44e7a056c25f4769148a15b",
+      "path": "grafting_v1/control/reconstruction.json",
+      "size_verified": true
+    },
+    "evidence": {
+      "repo": "arcadia-impact/scimt-dispatch-grafting-v1",
+      "repo_type": "dataset",
+      "revision": "5b2ffc08fcf578a4897c6b2ce74f8d1592af74d3",
+      "prefix": "runs/20260819T132410Z/control",
+      "files": 33,
+      "sizes_verified": true,
+      "lfs_sha256_verified": true,
+      "last_retry_error": null
+    }
+  },
+  "published_full_weights": false,
+  "retained_adapter_checkpoints": {
+    "sdf": [],
+    "aft": [
+      512
+    ]
+  },
+  "evaluated_endpoints": [
+    "pre_aft",
+    "post_aft"
+  ],
+  "final_evidence_revision": "78d1b63216a9a65113c3a0d84e94c75dfcef1be8"
+}