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 6 days ago

Commit

0cd43e9

verified ·

1 Parent(s): 407143d

verify aft_elicitation_v1/charter_real_4x__baseline/results

Browse files

Files changed (1) hide show

aft_elicitation_v1/charter_real_4x__baseline/results/ARTIFACT_MANIFEST.json +71 -0

aft_elicitation_v1/charter_real_4x__baseline/results/ARTIFACT_MANIFEST.json ADDED Viewed

	@@ -0,0 +1,71 @@

+{
+  "repo": "arcadia-impact/scimt-dispatch-models",
+  "remote_prefix": "aft_elicitation_v1/charter_real_4x__baseline/results",
+  "local_folder": "/workspace/elicit/gpu0/results/charter_real_4x__baseline-baseline",
+  "files": {
+    "eval_holdout_adjacent.jsonl": {
+      "size": 48447,
+      "sha256": "f0e3b781755df2461e7d835ecca1ce26f57b6a182866e2697abd95a24e9433ba"
+    },
+    "eval_holdout_agreement.jsonl": {
+      "size": 92866,
+      "sha256": "399d982fd6331111f8592b41940e3747e42411102f3b7c59412c641e07a68a06"
+    },
+    "eval_holdout_conflict.jsonl": {
+      "size": 92079,
+      "sha256": "e34dedec12649f157d77442e936746c99ef3f6d59e7ccb393b8d1822aa167c46"
+    },
+    "eval_trained_adjacent.jsonl": {
+      "size": 121155,
+      "sha256": "aeafe3c1759c7e275d00a4aa40d07ee8112425ffc29c04950b57cd8bfb9a6c76"
+    },
+    "eval_trained_agreement.jsonl": {
+      "size": 232226,
+      "sha256": "56186136ed0bb4a769ded9c38c69ee187c590cbaea0dfdaca30058973b7e8328"
+    },
+    "eval_trained_conflict.jsonl": {
+      "size": 230213,
+      "sha256": "48ff87b6a6599ea72d36e91b029a20e16237a92f629c7ad24b7ab641bf255db1"
+    },
+    "instr_charter_name__trained_agreement.jsonl": {
+      "size": 232252,
+      "sha256": "3160ac8c2934847f08abc8e311038e896c48a21d8ab42fee512bc5cb52994d0c"
+    },
+    "instr_charter_name__trained_conflict.jsonl": {
+      "size": 230210,
+      "sha256": "efae744e4b3b2669ba4d276a1e5ad1eefae95acd9a9168fecdc1a1613c471885"
+    },
+    "instr_charter_text__trained_agreement.jsonl": {
+      "size": 232228,
+      "sha256": "d1430f443e9220d0414ead8e8e02d9fe79cb770c6242bc0faa103ab4d209a15a"
+    },
+    "instr_charter_text__trained_conflict.jsonl": {
+      "size": 230220,
+      "sha256": "68e7b4d0f3e824d3792b8f85f83ef9b528d1cfb1dc0558378a1ca709d610e9ef"
+    },
+    "instr_profit__trained_agreement.jsonl": {
+      "size": 232235,
+      "sha256": "21835816f9a7bf76b3cfbd8ad34c5464415b220feec42350d7676d0da225c756"
+    },
+    "instr_profit__trained_conflict.jsonl": {
+      "size": 230191,
+      "sha256": "0cd7641aec36ffc1eea0cc74a58958d859124b4a35c37ecab02713ea809b59e4"
+    },
+    "recall_forced_choice.jsonl": {
+      "size": 8196,
+      "sha256": "e508575e4dc210b1d358d9f1b044e6300e0b47557dce23dc5ed42d5ccc4e36da"
+    },
+    "recall_freeform.jsonl": {
+      "size": 4086,
+      "sha256": "f08098545b87be02e920847b713985f2f869b32ded56107e6471992032d40cb8"
+    },
+    "sanity.jsonl": {
+      "size": 6450,
+      "sha256": "90acbf15d330eab054bc6195daed5cd1c2960f52dd7b4e949037f6469e242dc9"
+    },
+    "sanity_prompts.jsonl": {
+      "size": 154858,
+      "sha256": "9b5e3d3a725004127c0681dc9abe20650c2177c1fa19941c8630ffa6fa99c82d"
+    }
+  }
+}