Instructions to use nuprl/MultiPL-T-StarCoderBase_1b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use nuprl/MultiPL-T-StarCoderBase_1b with Transformers:

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

pipe = pipeline("text-generation", model="nuprl/MultiPL-T-StarCoderBase_1b")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("nuprl/MultiPL-T-StarCoderBase_1b")
model = AutoModelForCausalLM.from_pretrained("nuprl/MultiPL-T-StarCoderBase_1b")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use nuprl/MultiPL-T-StarCoderBase_1b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "nuprl/MultiPL-T-StarCoderBase_1b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "nuprl/MultiPL-T-StarCoderBase_1b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/nuprl/MultiPL-T-StarCoderBase_1b

SGLang

How to use nuprl/MultiPL-T-StarCoderBase_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 "nuprl/MultiPL-T-StarCoderBase_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": "nuprl/MultiPL-T-StarCoderBase_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 "nuprl/MultiPL-T-StarCoderBase_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": "nuprl/MultiPL-T-StarCoderBase_1b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use nuprl/MultiPL-T-StarCoderBase_1b with Docker Model Runner:
```
docker model run hf.co/nuprl/MultiPL-T-StarCoderBase_1b
```

cassanof commited on Aug 19, 2023

Commit

b4a4d34

1 Parent(s): fba8015

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+---
+license: bigscience-openrail-m
+datasets:
+- nuprl/MultiPL-T
+metrics:
+- code_eval
+library_name: transformers
+tags:
+- code
+- gpt_bigcode
+---
+# MultiPLCoder-1b
+State-of-the-art StarCoder-based models for low-resource languages
+## Language Revision Index
+This is the revision index for the best-performing models on their respective HumanEval benchmarks.
+| Langauge      | Revision ID | Epoch |
+| ------------- | ----------- | ----- |
+| Lua           | `7e96d931547e342ad0661cdd91236fe4ccf52545`         | 3    |
+| Racket           | `2cdc541bee1db4da80c0b43384b0d6a0cacca5b2`         | 5    |
+| OCaml           | `e8a24f9e2149cbda8c3cca264a53c2b361b7a031`         | 6 |
+## Usage
+To utilize one of the models in this repository, you must first select a commit revision for that model.