Instructions to use sraivante/superfast-tiny-home-robotics-json-1m-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use sraivante/superfast-tiny-home-robotics-json-1m-v1 with Transformers:

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

pipe = pipeline("text-generation", model="sraivante/superfast-tiny-home-robotics-json-1m-v1")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("sraivante/superfast-tiny-home-robotics-json-1m-v1")
model = AutoModelForCausalLM.from_pretrained("sraivante/superfast-tiny-home-robotics-json-1m-v1", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=256)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use sraivante/superfast-tiny-home-robotics-json-1m-v1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "sraivante/superfast-tiny-home-robotics-json-1m-v1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "sraivante/superfast-tiny-home-robotics-json-1m-v1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/sraivante/superfast-tiny-home-robotics-json-1m-v1

SGLang

How to use sraivante/superfast-tiny-home-robotics-json-1m-v1 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 "sraivante/superfast-tiny-home-robotics-json-1m-v1" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "sraivante/superfast-tiny-home-robotics-json-1m-v1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "sraivante/superfast-tiny-home-robotics-json-1m-v1" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "sraivante/superfast-tiny-home-robotics-json-1m-v1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use sraivante/superfast-tiny-home-robotics-json-1m-v1 with Docker Model Runner:
```
docker model run hf.co/sraivante/superfast-tiny-home-robotics-json-1m-v1
```

superfast-tiny-home-robotics-json-1m-v1 / tokenizer.json

sraivante

Release v1.0.0: reproducible home-command model

f2d0f42 verified 16 days ago

Raw History Blame Contribute Delete

54.9 kB

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	"ur",
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	"E",
	"LEVISION"
	],
	[
	"ĠT",
	"ELEVISION"
	],
	[
	"B",
	"ro"
	],
	[
	"Ġgaan",
	"e"
	],
	[
	"B",
	"E"
	],
	[
	"U",
	"BE"
	],
	[
	"L",
	"B"
	],
	[
	"U",
	"LB"
	],
	[
	"B",
	"R"
	],
	[
	"BR",
	"O"
	],
	[
	"DE",
	"SER"
	],
	[
	"DESER",
	"T"
	],
	[
	"A",
	"B"
	],
	[
	"AB",
	"LE"
	],
	[
	"ĠB",
	"ULB"
	],
	[
	"ĠT",
	"UBE"
	],
	[
	"Ġ",
	"DESERT"
	],
	[
	"ĠT",
	"ABLE"
	],
	[
	"o",
	"me"
	],
	[
	"Ġs",
	"ome"
	],
	[
	"S",
	"T"
	],
	[
	"ĠLIGHT",
	"S"
	],
	[
	"Ġla",
	"wn"
	],
	[
	"e",
	"i"
	],
	[
	"l",
	"ing"
	],
	[
	"Ġc",
	"ei"
	],
	[
	"Ġcei",
	"ling"
	],
	[
	"h",
	"ot"
	],
	[
	"Ġ",
	"hot"
	],
	[
	"o",
	"m"
	],
	[
	"Ġro",
	"om"
	],
	[
	"Ġ",
	"wash"
	],
	[
	"Ġwash",
	"er"
	],
	[
	"E",
	"E"
	],
	[
	"G",
	"EE"
	],
	[
	"AN",
	"GEE"
	],
	[
	"ANGEE",
	"T"
	],
	[
	"Ġ",
	"heat"
	],
	[
	"Ġheat",
	"er"
	],
	[
	"U",
	"DHON"
	],
	[
	"Ġ",
	"laundry"
	],
	[
	"H",
	"AT"
	],
	[
	"ĠS",
	"ANGEET"
	],
	[
	"ĠPA",
	"UDHON"
	],
	[
	"GH",
	"AR"
	],
	[
	"g",
	"s"
	],
	[
	"on",
	"gs"
	],
	[
	"Ġs",
	"ongs"
	],
	[
	"Ġ",
	"DHON"
	],
	[
	"AL",
	"I"
	],
	[
	"ĠW",
	"ALI"
	],
	[
	"ĠDHON",
	"E"
	],
	[
	"c",
	"on"
	],
	[
	"Ġair",
	"con"
	],
	[
	"AT",
	"US"
	],
	[
	"ĠCH",
	"HAT"
	],
	[
	"Ġ",
	"GHAR"
	],
	[
	"ĠGAAN",
	"A"
	],
	[
	"P",
	"DE"
	],
	[
	"ĠKA",
	"PDE"
	],
	[
	"ST",
	"ATUS"
	],
	[
	"A",
	"G"
	],
	[
	"IC",
	"HE"
	],
	[
	"AG",
	"ICHE"
	],
	[
	"ĠB",
	"AGICHE"
	],
	[
	"ĠGAAN",
	"E"
	],
	[
	"Ġ",
	"H"
	],
	[
	"O",
	"ME"
	],
	[
	"ĠS",
	"OME"
	],
	[
	"HE",
	"R"
	],
	[
	"ĠWAS",
	"HER"
	],
	[
	"ĠH",
	"OT"
	],
	[
	"ĠR",
	"OO"
	],
	[
	"ĠROO",
	"M"
	],
	[
	"E",
	"I"
	],
	[
	"L",
	"ING"
	],
	[
	"ĠC",
	"EI"
	],
	[
	"ĠCEI",
	"LING"
	],
	[
	"ĠLA",
	"WN"
	],
	[
	"Ġ",
	"HE"
	],
	[
	"ĠHE",
	"ATER"
	],
	[
	"D",
	"R"
	],
	[
	"UN",
	"DR"
	],
	[
	"ĠLA",
	"UNDR"
	],
	[
	"ĠLAUNDR",
	"Y"
	],
	[
	"t",
	"art"
	],
	[
	"C",
	"ON"
	],
	[
	"ĠAIR",
	"CON"
	],
	[
	"G",
	"S"
	],
	[
	"ON",
	"GS"
	],
	[
	"ĠS",
	"ONGS"
	],
	[
	"ur",
	"n"
	],
	[
	"a",
	"ani"
	],
	[
	"t",
	"op"
	],
	[
	"P",
	"A"
	],
	[
	"am",
	"re"
	],
	[
	"ank",
	"i"
	],
	[
	"s",
	"tart"
	],
	[
	"p",
	"ower"
	],
	[
	"P",
	"OWER"
	],
	[
	"ST",
	"ART"
	],
	[
	"P",
	"ower"
	],
	[
	"sh",
	"ut"
	],
	[
	"S",
	"h"
	],
	[
	"Sh",
	"ut"
	],
	[
	"S",
	"tart"
	],
	[
	"H",
	"UT"
	],
	[
	"S",
	"HUT"
	],
	[
	"s",
	"witch"
	],
	[
	"S",
	"WITCH"
	],
	[
	"S",
	"witch"
	],
	[
	"t",
	"urn"
	],
	[
	"PA",
	"ANI"
	],
	[
	"p",
	"aani"
	],
	[
	"Ġ",
	"hai"
	],
	[
	"T",
	"UR"
	],
	[
	"TUR",
	"N"
	],
	[
	"T",
	"urn"
	],
	[
	"P",
	"aani"
	],
	[
	"at",
	"us"
	],
	[
	"Ġst",
	"atus"
	],
	[
	"a",
	"udhon"
	],
	[
	"K",
	"AM"
	],
	[
	"KAM",
	"RE"
	],
	[
	"c",
	"k"
	],
	[
	"S",
	"P"
	],
	[
	"p",
	"ani"
	],
	[
	"G",
	"ARAM"
	],
	[
	"S",
	"p"
	],
	[
	"s",
	"top"
	],
	[
	"R",
	"un"
	],
	[
	"Ġk",
	"ya"
	],
	[
	"R",
	"UN"
	],
	[
	"P",
	"ANI"
	],
	[
	"k",
	"amre"
	],
	[
	"ap",
	"de"
	],
	[
	"ST",
	"OP"
	],
	[
	"P",
	"ani"
	],
	[
	"G",
	"ara"
	],
	[
	"Gara",
	"m"
	],
	[
	"S",
	"top"
	],
	[
	"r",
	"un"
	],
	[
	"K",
	"amre"
	],
	[
	"T",
	"anki"
	],
	[
	"t",
	"anki"
	],
	[
	"Ġi",
	"s"
	],
	[
	"T",
	"ANK"
	],
	[
	"TANK",
	"I"
	],
	[
	"G",
	"a"
	],
	[
	"Ga",
	"an"
	],
	[
	"P",
	"ut"
	],
	[
	"P",
	"UT"
	],
	[
	"p",
	"ut"
	],
	[
	"e",
	"ck"
	],
	[
	"Ġch",
	"eck"
	],
	[
	"a",
	"ha"
	]
	]
	}
	}