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 4 days ago

Commit

e10c027

verified ·

1 Parent(s): 6c9ffb3

archive control adapters from run 20260826T001500Z (trained in wave 1 but never evaluated (tied lm_head eval failure); wave 2 retrains the cell to obtain the step-128 endpoint)

Browse files

Files changed (17) hide show

graft_dose_v1/control/superseded/20260826T001500Z/SUPERSEDED.json +28 -0
graft_dose_v1/control/superseded/20260826T001500Z/aft_charter0p2_adapter/ARTIFACT_MANIFEST.json +19 -0
graft_dose_v1/control/superseded/20260826T001500Z/aft_charter0p2_adapter/TRAINING.json +46 -0
graft_dose_v1/control/superseded/20260826T001500Z/aft_charter0p2_adapter/adapter_config.json +48 -0
graft_dose_v1/control/superseded/20260826T001500Z/aft_charter0p2_adapter/adapter_model.safetensors +3 -0
graft_dose_v1/control/superseded/20260826T001500Z/aft_charter2_adapter/ARTIFACT_MANIFEST.json +19 -0
graft_dose_v1/control/superseded/20260826T001500Z/aft_charter2_adapter/TRAINING.json +46 -0
graft_dose_v1/control/superseded/20260826T001500Z/aft_charter2_adapter/adapter_config.json +48 -0
graft_dose_v1/control/superseded/20260826T001500Z/aft_charter2_adapter/adapter_model.safetensors +3 -0
graft_dose_v1/control/superseded/20260826T001500Z/aft_coin0p2_adapter/ARTIFACT_MANIFEST.json +19 -0
graft_dose_v1/control/superseded/20260826T001500Z/aft_coin0p2_adapter/TRAINING.json +46 -0
graft_dose_v1/control/superseded/20260826T001500Z/aft_coin0p2_adapter/adapter_config.json +48 -0
graft_dose_v1/control/superseded/20260826T001500Z/aft_coin0p2_adapter/adapter_model.safetensors +3 -0
graft_dose_v1/control/superseded/20260826T001500Z/aft_coin2_adapter/ARTIFACT_MANIFEST.json +19 -0
graft_dose_v1/control/superseded/20260826T001500Z/aft_coin2_adapter/TRAINING.json +46 -0
graft_dose_v1/control/superseded/20260826T001500Z/aft_coin2_adapter/adapter_config.json +48 -0
graft_dose_v1/control/superseded/20260826T001500Z/aft_coin2_adapter/adapter_model.safetensors +3 -0

graft_dose_v1/control/superseded/20260826T001500Z/SUPERSEDED.json ADDED Viewed

	@@ -0,0 +1,28 @@

+{
+  "schema_version": "scimt_superseded_adapters_v1",
+  "parent": "control",
+  "published_by_run": "20260826T001500Z",
+  "reason": "trained in wave 1 but never evaluated (tied lm_head eval failure); wave 2 retrains the cell to obtain the step-128 endpoint",
+  "adapters": {
+    "coin2": {
+      "original_prefix": "graft_dose_v1/control/aft_coin2_adapter",
+      "archived_prefix": "graft_dose_v1/control/superseded/20260826T001500Z/aft_coin2_adapter",
+      "tree_sha256": "4bdc9e107468cabad59a72d7fc4bd1d4b2623e092affdd1b5e2676a83f8a796e"
+    },
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+      "archived_prefix": "graft_dose_v1/control/superseded/20260826T001500Z/aft_charter2_adapter",
+      "tree_sha256": "8d32e192c61d55f90d3a85b19288dc6e2ffcb3f261f9bf01222b97e6903ed161"
+    },
+    "coin0p2": {
+      "original_prefix": "graft_dose_v1/control/aft_coin0p2_adapter",
+      "archived_prefix": "graft_dose_v1/control/superseded/20260826T001500Z/aft_coin0p2_adapter",
+      "tree_sha256": "fd85fa31c453ef017d80383ada6d1b74af14829781223ee573357fe028bcdd09"
+    },
+    "charter0p2": {
+      "original_prefix": "graft_dose_v1/control/aft_charter0p2_adapter",
+      "archived_prefix": "graft_dose_v1/control/superseded/20260826T001500Z/aft_charter0p2_adapter",
+      "tree_sha256": "a9e0966eae8c4b0900e5d407dadf36276835e722cb5bbfbb5668ee62a6e67cdf"
+    }
+  }
+}

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+      "sha256": "adf0cd9e7fafef46ff0534367981daadba6bf569a2e47b733992a5ad84ac4635"
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+  "version": "dispatch_graft_dose_v1",
+  "label": "control",
+  "phase": "aft_charter0p2",
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+  "seconds_per_step": 7.899,
+  "completed_at": "2026-08-26T03:48:54+00:00"
+}

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+  "alpha_pattern": {},
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+  "lora_dropout": 0.05,
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+  "megatron_config": null,
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+  "schema_version": "scimt_adapter_artifact_manifest_v1",
+  "name": "aft_charter2",
+  "files": {
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graft_dose_v1/control/superseded/20260826T001500Z/aft_charter2_adapter/TRAINING.json ADDED Viewed

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+{
+  "schema_version": "dispatch_graft_dose_training_v1",
+  "version": "dispatch_graft_dose_v1",
+  "label": "control",
+  "phase": "aft_charter2",
+  "stage": "aft_dispatch_graft_dose_1ep_gemma3_12b",
+  "seed": 42,
+  "dataset_sha256": "6a1f783d80a3d91f3aea0f9e8fb701f65f1e60162ac5be0f24db62b3c7612b57",
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+    "triton_kernels": false,
+    "initial_adapter_path": null
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+}

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+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": null,
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+{
+  "schema_version": "scimt_adapter_artifact_manifest_v1",
+  "name": "aft_coin0p2",
+  "files": {
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graft_dose_v1/control/superseded/20260826T001500Z/aft_coin0p2_adapter/TRAINING.json ADDED Viewed

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+{
+  "schema_version": "dispatch_graft_dose_training_v1",
+  "version": "dispatch_graft_dose_v1",
+  "label": "control",
+  "phase": "aft_coin0p2",
+  "stage": "aft_dispatch_graft_dose_1ep_gemma3_12b",
+  "seed": 42,
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+    ],
+    "target_parameters": null,
+    "triton_kernels": false,
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+  },
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+  ],
+  "required_checkpoints": [
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+  ],
+  "adapter_payload_audit": {
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+    "nonzero_lora_b": true,
+    "vision_tensor_count": 162,
+    "audited_exact_targets": null
+  },
+  "minutes": 33.877,
+  "seconds_per_step": 7.94,
+  "completed_at": "2026-08-26T03:14:46+00:00"
+}

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+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/hf-graft-dose/hub/models--arcadia-impact--scimt-dispatch-models/snapshots/dfdd164dad975c0d71ccedb14337927fe60c10ad/gate2_midtrain4/dolmino/post_dolci100",
+  "bias": "none",
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+  "modules_to_save": null,
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+}

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+{
+  "schema_version": "scimt_adapter_artifact_manifest_v1",
+  "name": "aft_coin2",
+  "files": {
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graft_dose_v1/control/superseded/20260826T001500Z/aft_coin2_adapter/TRAINING.json ADDED Viewed

	@@ -0,0 +1,46 @@

+{
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+  "version": "dispatch_graft_dose_v1",
+  "label": "control",
+  "phase": "aft_coin2",
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+  "completed_at": "2026-08-26T02:06:06+00:00"
+}

graft_dose_v1/control/superseded/20260826T001500Z/aft_coin2_adapter/adapter_config.json ADDED Viewed

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+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
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+  "use_qalora": false,
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+}

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