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 5 days ago

Commit

ae19ac2

verified ·

1 Parent(s): 75490d3

dispatch-sdf-aft-v1: aft_elicitation_v1/charter_real_4x__name_coin2/CELL_COMPLETE.json

Browse files

Files changed (1) hide show

aft_elicitation_v1/charter_real_4x__name_coin2/CELL_COMPLETE.json +47 -0

aft_elicitation_v1/charter_real_4x__name_coin2/CELL_COMPLETE.json ADDED Viewed

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

+{
+  "version": "dispatch_elicitation_v1",
+  "arm": "charter_real_4x__name_coin2",
+  "kind": "train",
+  "dataset": "name_coin2",
+  "parameterization": "lora",
+  "parent_repo": "arcadia-impact/scimt-dispatch-models",
+  "parent_revision": "9ac77232d7efa44bb8f951ff88954c3dc914f64d",
+  "data_repo": "arcadia-impact/scimt-dispatch-aft-data",
+  "data_prefix": "extensions/elicitation_v1/data",
+  "data_revision": "177d2d84241935c15a7e7d76ed9e947d39852d1f",
+  "dataset_sha256": "729fc48703863f7b5ecf08224c18acc0ce91814585cf9c056c579c3331725cb2",
+  "training_rows": 8192,
+  "stage": "aft_dispatch_v4_wide_final",
+  "seed": 42,
+  "minutes": 67.23,
+  "lora": {
+    "r": 32,
+    "alpha": 64,
+    "dropout": 0.05,
+    "target_linear": false,
+    "target_modules": [
+      "q_proj",
+      "k_proj",
+      "v_proj",
+      "o_proj",
+      "gate_proj",
+      "up_proj",
+      "down_proj"
+    ],
+    "target_parameters": null,
+    "triton_kernels": false,
+    "initial_adapter_path": null
+  },
+  "optimizer_steps": 512,
+  "checkpoint_upload": {
+    "repo": "arcadia-impact/scimt-dispatch-models",
+    "remote_prefix": "aft_elicitation_v1/charter_real_4x__name_coin2/training/checkpoints/checkpoint-512",
+    "revision": "75490d37f4c6e54379aac7a9eb3827ca80704ba9",
+    "n_files": 9,
+    "sizes_verified": true,
+    "sha256_manifest_uploaded": true,
+    "verified": true,
+    "last_error": null
+  },
+  "recovered_by": "elicitation_v1_persist_adapters.py"
+}