Instructions to use cloudsurf-software/CloudSurf-1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use cloudsurf-software/CloudSurf-1B with Transformers:

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

pipe = pipeline("text-generation", model="cloudsurf-software/CloudSurf-1B")

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

tokenizer = AutoTokenizer.from_pretrained("cloudsurf-software/CloudSurf-1B")
model = AutoModelForCausalLM.from_pretrained("cloudsurf-software/CloudSurf-1B", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use cloudsurf-software/CloudSurf-1B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "cloudsurf-software/CloudSurf-1B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "cloudsurf-software/CloudSurf-1B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/cloudsurf-software/CloudSurf-1B

SGLang

How to use cloudsurf-software/CloudSurf-1B 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 "cloudsurf-software/CloudSurf-1B" \
    --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": "cloudsurf-software/CloudSurf-1B",
		"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 "cloudsurf-software/CloudSurf-1B" \
        --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": "cloudsurf-software/CloudSurf-1B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use cloudsurf-software/CloudSurf-1B with Docker Model Runner:
```
docker model run hf.co/cloudsurf-software/CloudSurf-1B
```

brady777 commited on 12 days ago

Commit

4c7e5d0

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1 Parent(s): 960423c

Card copy: CloudSurf built every part of it

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@@ -19,7 +19,7 @@ inference: false
 # CloudSurf-1B
-CloudSurf-1B is a 0.89-billion-parameter base language model trained from random weights by CloudSurf Software LLC. CloudSurf owns every part of it: the tokenizer, the trainer, the corpus pipeline and the weights. It is the on-device tier of Surfy, CloudSurf's assistant. It runs on a phone or a laptop with no network and no per-token cost. Its jobs there are routing requests, writing SurfDoc, and answering when the device is offline. It hands harder work to larger models.
 This release is the **base** checkpoint. It is not instruction-tuned and has no tool-calling tune. Those come in the next step (the rung tune), which has its own pre-registration.

 # CloudSurf-1B
+CloudSurf-1B is a 0.89-billion-parameter base language model trained from random weights by CloudSurf Software LLC. CloudSurf built every part of it: the tokenizer, the trainer, the corpus pipeline and the weights. It is the on-device tier of Surfy, CloudSurf's assistant. It runs on a phone or a laptop with no network and no per-token cost. Its jobs there are routing requests, writing SurfDoc, and answering when the device is offline. It hands harder work to larger models.
 This release is the **base** checkpoint. It is not instruction-tuned and has no tool-calling tune. Those come in the next step (the rung tune), which has its own pre-registration.