Instructions to use abacaj/starcoderbase-1b-sft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use abacaj/starcoderbase-1b-sft with Transformers:

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

pipe = pipeline("text-generation", model="abacaj/starcoderbase-1b-sft")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("abacaj/starcoderbase-1b-sft")
model = AutoModelForCausalLM.from_pretrained("abacaj/starcoderbase-1b-sft")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use abacaj/starcoderbase-1b-sft with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "abacaj/starcoderbase-1b-sft"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "abacaj/starcoderbase-1b-sft",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/abacaj/starcoderbase-1b-sft

SGLang

How to use abacaj/starcoderbase-1b-sft 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 "abacaj/starcoderbase-1b-sft" \
    --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": "abacaj/starcoderbase-1b-sft",
		"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 "abacaj/starcoderbase-1b-sft" \
        --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": "abacaj/starcoderbase-1b-sft",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use abacaj/starcoderbase-1b-sft with Docker Model Runner:
```
docker model run hf.co/abacaj/starcoderbase-1b-sft
```

abacaj commited on Sep 6, 2023

Commit

b4eeeb5

1 Parent(s): 1f615d1

Update README.md

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@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: pass@1
       type: pass@1
-      value: 24.1
       verified: false
 language:
 - en
@@ -78,7 +78,7 @@ if __name__ == "__main__":
 ```
 Evals:
-![image/png](https://cdn-uploads.huggingface.co/production/uploads/62ceeb27e7f6014c0e9d9268/_i-IkouWb1qMz8c9LXB7M.png)
 Training charts:
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/62ceeb27e7f6014c0e9d9268/PLkFqE7_34-hJmFW7_opG.png)

     metrics:
     - name: pass@1
       type: pass@1
+      value: 31.74
       verified: false
 language:
 - en
 ```
 Evals:
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/62ceeb27e7f6014c0e9d9268/U7L1aOV7UxBEBcLGqOZ2s.png)
 Training charts:
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/62ceeb27e7f6014c0e9d9268/PLkFqE7_34-hJmFW7_opG.png)