Instructions to use TechxGenus/starcoder2-3b-instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TechxGenus/starcoder2-3b-instruct with Transformers:

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

pipe = pipeline("text-generation", model="TechxGenus/starcoder2-3b-instruct")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("TechxGenus/starcoder2-3b-instruct")
model = AutoModelForCausalLM.from_pretrained("TechxGenus/starcoder2-3b-instruct")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use TechxGenus/starcoder2-3b-instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "TechxGenus/starcoder2-3b-instruct"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "TechxGenus/starcoder2-3b-instruct",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/TechxGenus/starcoder2-3b-instruct

SGLang

How to use TechxGenus/starcoder2-3b-instruct 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 "TechxGenus/starcoder2-3b-instruct" \
    --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": "TechxGenus/starcoder2-3b-instruct",
		"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 "TechxGenus/starcoder2-3b-instruct" \
        --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": "TechxGenus/starcoder2-3b-instruct",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use TechxGenus/starcoder2-3b-instruct with Docker Model Runner:
```
docker model run hf.co/TechxGenus/starcoder2-3b-instruct
```

starcoder2-3b-instruct / special_tokens_map.json

TechxGenus

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	{
	"additional_special_tokens": [
	"<\|endoftext\|>",
	"<fim_prefix>",
	"<fim_middle>",
	"<fim_suffix>",
	"<fim_pad>",
	"<repo_name>",
	"<file_sep>",
	"<issue_start>",
	"<issue_comment>",
	"<issue_closed>",
	"<jupyter_start>",
	"<jupyter_text>",
	"<jupyter_code>",
	"<jupyter_output>",
	"<jupyter_script>",
	"<empty_output>",
	"<code_to_intermediate>",
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	"<pr>",
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	"<pr_diff>",
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	"<pr_comment>",
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	"<pr_in_reply_to_comment_id>",
	"<pr_diff_hunk_comment_line>",
	"<NAME>",
	"<EMAIL>",
	"<KEY>",
	"<PASSWORD>"
	],
	"bos_token": {
	"content": "<\|endoftext\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false
	},
	"eos_token": {
	"content": "<\|endoftext\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false
	},
	"pad_token": "<\|endoftext\|>",
	"unk_token": {
	"content": "<\|endoftext\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false
	}
	}