Instructions to use Nanthasit/sakthai-plus-1.5b-coder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Nanthasit/sakthai-plus-1.5b-coder with Transformers:

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

pipe = pipeline("text-generation", model="Nanthasit/sakthai-plus-1.5b-coder")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Nanthasit/sakthai-plus-1.5b-coder", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Nanthasit/sakthai-plus-1.5b-coder with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Nanthasit/sakthai-plus-1.5b-coder"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Nanthasit/sakthai-plus-1.5b-coder",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Nanthasit/sakthai-plus-1.5b-coder

SGLang

How to use Nanthasit/sakthai-plus-1.5b-coder 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 "Nanthasit/sakthai-plus-1.5b-coder" \
    --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": "Nanthasit/sakthai-plus-1.5b-coder",
		"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 "Nanthasit/sakthai-plus-1.5b-coder" \
        --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": "Nanthasit/sakthai-plus-1.5b-coder",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Nanthasit/sakthai-plus-1.5b-coder with Docker Model Runner:
```
docker model run hf.co/Nanthasit/sakthai-plus-1.5b-coder
```

sakthai-plus-1.5b-coder

Commit History

docs: improve README front matter, status, usage snippets, benchmarks, limitations

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fix: remove phantom combined-v10 references

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docs: expand model card with description, usage, training config, architecture, benchmarks, limitations, citation

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eval: cron metadata snapshot 20260801T000551Z

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feat(card): add model-index, dedicated sections, honest benchmark table, usage snippet

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fix(bibtex): close broken \url{} in citation block

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cron: add metadata eval snapshot cron-eval-sakthai-plus-1.5b-coder-2026-07-31-20260731T192915Z.yaml

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benchmark 20260731_192407: router probe 400 for Nanthasit/sakthai-plus-1.5b-coder

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cron: enriched skeleton card — plus 1.5B coder

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docs: add Limitations + Citation sections to model card

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cron: add eval result #1 for sakthai-plus-1.5b-coder (metadata_cron)

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docs: honest rewrite — repo is a skeleton/placeholder with no weights; add status banner, working alternatives, planned training config, full family table, eval status from .eval_results

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Fix dead cross-link: sakthai-combined-v8 (404) -> sakthai-combined-v10 (normalized v7+v8)

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