Instructions to use nuprl/MultiPL-T-StarCoderBase_15b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use nuprl/MultiPL-T-StarCoderBase_15b with Transformers:

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

pipe = pipeline("text-generation", model="nuprl/MultiPL-T-StarCoderBase_15b")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("nuprl/MultiPL-T-StarCoderBase_15b")
model = AutoModelForCausalLM.from_pretrained("nuprl/MultiPL-T-StarCoderBase_15b")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use nuprl/MultiPL-T-StarCoderBase_15b 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_15b"
# 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_15b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/nuprl/MultiPL-T-StarCoderBase_15b

SGLang

How to use nuprl/MultiPL-T-StarCoderBase_15b 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_15b" \
    --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_15b",
		"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_15b" \
        --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_15b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use nuprl/MultiPL-T-StarCoderBase_15b with Docker Model Runner:
```
docker model run hf.co/nuprl/MultiPL-T-StarCoderBase_15b
```

cassanof commited on Oct 23, 2023

Commit

eee3c5e

1 Parent(s): 9ee64ae

model_starcoder15b_multiplt_jl-epoch1

Browse files

Files changed (6) hide show

config.json +2 -2
generation_config.json +1 -1
pytorch_model-00001-of-00004.bin +1 -1
pytorch_model-00002-of-00004.bin +1 -1
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pytorch_model-00004-of-00004.bin +1 -1

config.json CHANGED Viewed

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "model_starcoder15b_all_lang_equal_paper/checkpoint-2600",
   "activation_function": "gelu",
   "architectures": [
     "GPTBigCodeForCausalLM"
@@ -32,7 +32,7 @@
   "summary_type": "cls_index",
   "summary_use_proj": true,
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-  "transformers_version": "4.31.0",
   "use_cache": false,
   "validate_runner_input": true,
   "vocab_size": 49152

 {
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   "activation_function": "gelu",
   "architectures": [
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   "summary_type": "cls_index",
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   "validate_runner_input": true,
   "vocab_size": 49152

generation_config.json CHANGED Viewed

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 }

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