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

Libraries

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

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

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

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

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

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

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

Install from pip and serve model

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

Use Docker

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

SGLang

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

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

Yik commited on Mar 4, 2024

Commit

9b4e885

verified ·

1 Parent(s): 107ed20

Training in progress, step 1500

Browse files

Files changed (1) hide show

runs/Mar04_15-53-28_606cf3968c2b/events.out.tfevents.1709567620.606cf3968c2b.193.0 +2 -2

runs/Mar04_15-53-28_606cf3968c2b/events.out.tfevents.1709567620.606cf3968c2b.193.0 CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:f70ee7bd42e899423c2a3ad16771fefdf8a547980527cbdee102dd34ad3944ad
-size 26808

 version https://git-lfs.github.com/spec/v1
+oid sha256:9e4e5b34edeaa6d0926ef5a609421ffe0ce9b0981976ef3f2b3070337efeffb8
+size 37629