Instructions to use Kukedlc/NeuralSynthesis-7b-v0.4-slerp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Kukedlc/NeuralSynthesis-7b-v0.4-slerp with Transformers:

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

pipe = pipeline("text-generation", model="Kukedlc/NeuralSynthesis-7b-v0.4-slerp")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Kukedlc/NeuralSynthesis-7b-v0.4-slerp")
model = AutoModelForCausalLM.from_pretrained("Kukedlc/NeuralSynthesis-7b-v0.4-slerp")

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Kukedlc/NeuralSynthesis-7b-v0.4-slerp with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Kukedlc/NeuralSynthesis-7b-v0.4-slerp"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Kukedlc/NeuralSynthesis-7b-v0.4-slerp",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Kukedlc/NeuralSynthesis-7b-v0.4-slerp

SGLang

How to use Kukedlc/NeuralSynthesis-7b-v0.4-slerp 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 "Kukedlc/NeuralSynthesis-7b-v0.4-slerp" \
    --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": "Kukedlc/NeuralSynthesis-7b-v0.4-slerp",
		"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 "Kukedlc/NeuralSynthesis-7b-v0.4-slerp" \
        --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": "Kukedlc/NeuralSynthesis-7b-v0.4-slerp",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Kukedlc/NeuralSynthesis-7b-v0.4-slerp with Docker Model Runner:
```
docker model run hf.co/Kukedlc/NeuralSynthesis-7b-v0.4-slerp
```

NeuralSynthesis-7b-v0.4-slerp / sample_data /anscombe.json

Kukedlc

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	[
	{"Series":"I", "X":10.0, "Y":8.04},
	{"Series":"I", "X":8.0, "Y":6.95},
	{"Series":"I", "X":13.0, "Y":7.58},
	{"Series":"I", "X":9.0, "Y":8.81},
	{"Series":"I", "X":11.0, "Y":8.33},
	{"Series":"I", "X":14.0, "Y":9.96},
	{"Series":"I", "X":6.0, "Y":7.24},
	{"Series":"I", "X":4.0, "Y":4.26},
	{"Series":"I", "X":12.0, "Y":10.84},
	{"Series":"I", "X":7.0, "Y":4.81},
	{"Series":"I", "X":5.0, "Y":5.68},

	{"Series":"II", "X":10.0, "Y":9.14},
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	{"Series":"II", "X":5.0, "Y":4.74},

	{"Series":"III", "X":10.0, "Y":7.46},
	{"Series":"III", "X":8.0, "Y":6.77},
	{"Series":"III", "X":13.0, "Y":12.74},
	{"Series":"III", "X":9.0, "Y":7.11},
	{"Series":"III", "X":11.0, "Y":7.81},
	{"Series":"III", "X":14.0, "Y":8.84},
	{"Series":"III", "X":6.0, "Y":6.08},
	{"Series":"III", "X":4.0, "Y":5.39},
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	{"Series":"III", "X":7.0, "Y":6.42},
	{"Series":"III", "X":5.0, "Y":5.73},

	{"Series":"IV", "X":8.0, "Y":6.58},
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	{"Series":"IV", "X":8.0, "Y":7.71},
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	{"Series":"IV", "X":8.0, "Y":8.47},
	{"Series":"IV", "X":8.0, "Y":7.04},
	{"Series":"IV", "X":8.0, "Y":5.25},
	{"Series":"IV", "X":19.0, "Y":12.50},
	{"Series":"IV", "X":8.0, "Y":5.56},
	{"Series":"IV", "X":8.0, "Y":7.91},
	{"Series":"IV", "X":8.0, "Y":6.89}
	]