Instructions to use scrapegoat/Scrapegoat-Tiny-Coder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use scrapegoat/Scrapegoat-Tiny-Coder with Transformers:

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

pipe = pipeline("text-generation", model="scrapegoat/Scrapegoat-Tiny-Coder")

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("scrapegoat/Scrapegoat-Tiny-Coder", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use scrapegoat/Scrapegoat-Tiny-Coder with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/scrapegoat/Scrapegoat-Tiny-Coder

SGLang

How to use scrapegoat/Scrapegoat-Tiny-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 "scrapegoat/Scrapegoat-Tiny-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": "scrapegoat/Scrapegoat-Tiny-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 "scrapegoat/Scrapegoat-Tiny-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": "scrapegoat/Scrapegoat-Tiny-Coder",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use scrapegoat/Scrapegoat-Tiny-Coder with Docker Model Runner:
```
docker model run hf.co/scrapegoat/Scrapegoat-Tiny-Coder
```

Scrapegoat-Tiny-Coder / tokenizer_config.json

Nathan9

Upload 9 files

5216a17 verified 3 days ago

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	{
	"added_tokens_decoder": {
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	"163590": {
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	},
	"163591": {
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	"163598": {
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	"163603": {
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	"163838": {
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	},
	"additional_special_tokens": [
	"<\|im_end\|>",
	"<\|im_user\|>",
	"<\|im_assistant\|>",
	"<\|start_header_id\|>",
	"<\|end_header_id\|>",
	"[EOT]",
	"<\|im_system\|>",
	"<\|im_middle\|>",
	"<\|media_begin\|>",
	"<\|media_content\|>",
	"<\|media_end\|>",
	"<\|media_pad\|>"
	],
	"bos_token": "[BOS]",
	"clean_up_tokenization_spaces": false,
	"eos_token": "[EOS]",
	"model_max_length": 1000000000000000019884624838656,
	"pad_token": "[PAD]",
	"unk_token": "[UNK]",
	"tokenizer_class": "GigaKimiTokenizer",
	"auto_map": {
	"AutoTokenizer": [
	"tokenisation_gigakimi.GigaKimiTokenizer",
	null
	]
	}
	}