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

9093796

verified ·

1 Parent(s): d60ffc7

dispatch_graft_dose_v1: graft_dose_v1/coin_d0.5m/aft_charter0p2_adapter

Browse files

Files changed (4) hide show

graft_dose_v1/coin_d0.5m/aft_charter0p2_adapter/ARTIFACT_MANIFEST.json +19 -0
graft_dose_v1/coin_d0.5m/aft_charter0p2_adapter/TRAINING.json +50 -0
graft_dose_v1/coin_d0.5m/aft_charter0p2_adapter/adapter_config.json +48 -0
graft_dose_v1/coin_d0.5m/aft_charter0p2_adapter/adapter_model.safetensors +3 -0

graft_dose_v1/coin_d0.5m/aft_charter0p2_adapter/ARTIFACT_MANIFEST.json ADDED Viewed

	@@ -0,0 +1,19 @@

+{
+  "schema_version": "scimt_adapter_artifact_manifest_v1",
+  "name": "aft_charter0p2",
+  "files": {
+    "TRAINING.json": {
+      "size": 1138,
+      "sha256": "1f0458d8dd4b9da8faab24c234bc0baf91fb4451e6ae1bbc7033498f218fb9d8"
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+}

graft_dose_v1/coin_d0.5m/aft_charter0p2_adapter/TRAINING.json ADDED Viewed

	@@ -0,0 +1,50 @@

+{
+  "schema_version": "dispatch_graft_dose_training_v1",
+  "version": "dispatch_graft_dose_v1",
+  "label": "coin_d0.5m",
+  "phase": "aft_charter0p2",
+  "stage": "aft_dispatch_graft_dose_1ep_gemma3_12b",
+  "gpus": 1,
+  "seed": 42,
+  "dataset_sha256": "6f2abe5d436e4596e27efe35b8db0744754d10bb8894e3f1de8557d3fc31e893",
+  "lora": {
+    "r": 32,
+    "alpha": 64,
+    "dropout": 0.05,
+    "target_linear": false,
+    "target_modules": [
+      "q_proj",
+      "k_proj",
+      "v_proj",
+      "o_proj",
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+      "up_proj",
+      "down_proj"
+    ],
+    "target_parameters": null,
+    "triton_kernels": false,
+    "initial_adapter_path": null
+  },
+  "global_step": 256,
+  "optimizer_steps": null,
+  "retained_checkpoints": [
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+    256
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+  "required_checkpoints": [
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+  "adapter_payload_audit": {
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+    "lora_b_tensor_count": 417,
+    "nonzero_lora_b": true,
+    "vision_tensor_count": 162,
+    "audited_exact_targets": null
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+  "minutes": 33.658,
+  "seconds_per_step": 7.889,
+  "completed_at": "2026-08-26T16:07:49+00:00",
+  "checkpoint_step": 256,
+  "terminal_step": 256
+}

graft_dose_v1/coin_d0.5m/aft_charter0p2_adapter/adapter_config.json ADDED Viewed

	@@ -0,0 +1,48 @@

+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": null,
+  "base_model_name_or_path": "/workspace/runtime/dispatch-graft-dose-v1/20260826T125019Z/coin_d0.5m/temporary_merged/graft",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": null,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 64,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "lora_ga_config": null,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.19.1",
+  "qalora_group_size": 16,
+  "r": 32,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "gate_proj",
+    "k_proj",
+    "v_proj",
+    "up_proj",
+    "o_proj",
+    "q_proj",
+    "down_proj"
+  ],
+  "target_parameters": [],
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_bdlora": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

graft_dose_v1/coin_d0.5m/aft_charter0p2_adapter/adapter_model.safetensors ADDED Viewed

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