Instructions to use mrm8488/santacoder-finetuned-the-stack-bash-shell with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mrm8488/santacoder-finetuned-the-stack-bash-shell with Transformers:

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

pipe = pipeline("text-generation", model="mrm8488/santacoder-finetuned-the-stack-bash-shell", trust_remote_code=True)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("mrm8488/santacoder-finetuned-the-stack-bash-shell", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("mrm8488/santacoder-finetuned-the-stack-bash-shell", trust_remote_code=True)

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use mrm8488/santacoder-finetuned-the-stack-bash-shell with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "mrm8488/santacoder-finetuned-the-stack-bash-shell"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mrm8488/santacoder-finetuned-the-stack-bash-shell",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/mrm8488/santacoder-finetuned-the-stack-bash-shell

SGLang

How to use mrm8488/santacoder-finetuned-the-stack-bash-shell 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 "mrm8488/santacoder-finetuned-the-stack-bash-shell" \
    --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": "mrm8488/santacoder-finetuned-the-stack-bash-shell",
		"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 "mrm8488/santacoder-finetuned-the-stack-bash-shell" \
        --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": "mrm8488/santacoder-finetuned-the-stack-bash-shell",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use mrm8488/santacoder-finetuned-the-stack-bash-shell with Docker Model Runner:
```
docker model run hf.co/mrm8488/santacoder-finetuned-the-stack-bash-shell
```

mrm8488 commited on Feb 2, 2023

Commit

7a311bb

1 Parent(s): 1d4a0ae

Update README.md

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@@ -2,11 +2,15 @@
 license: openrail
 tags:
 - generated_from_trainer
 model-index:
 - name: santacoder-finetuned-the-stack-bash-shell
   results: []
 datasets:
-- bigcode/the-stack
 language:
 - code
 pipeline_tag: text-generation

 license: openrail
 tags:
 - generated_from_trainer
+- bash
+- shell
+- code
+- codegen
 model-index:
 - name: santacoder-finetuned-the-stack-bash-shell
   results: []
 datasets:
+- bigcode/the-stack-dedup
 language:
 - code
 pipeline_tag: text-generation