Instructions to use AdnanRiaz107/CodeBert-finetuned-the-stack-bash with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use AdnanRiaz107/CodeBert-finetuned-the-stack-bash with Transformers:

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

pipe = pipeline("text-generation", model="AdnanRiaz107/CodeBert-finetuned-the-stack-bash")

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

tokenizer = AutoTokenizer.from_pretrained("AdnanRiaz107/CodeBert-finetuned-the-stack-bash")
model = AutoModelForCausalLM.from_pretrained("AdnanRiaz107/CodeBert-finetuned-the-stack-bash", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use AdnanRiaz107/CodeBert-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 "AdnanRiaz107/CodeBert-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": "AdnanRiaz107/CodeBert-finetuned-the-stack-bash",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/AdnanRiaz107/CodeBert-finetuned-the-stack-bash

SGLang

How to use AdnanRiaz107/CodeBert-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 "AdnanRiaz107/CodeBert-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": "AdnanRiaz107/CodeBert-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 "AdnanRiaz107/CodeBert-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": "AdnanRiaz107/CodeBert-finetuned-the-stack-bash",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use AdnanRiaz107/CodeBert-finetuned-the-stack-bash with Docker Model Runner:
```
docker model run hf.co/AdnanRiaz107/CodeBert-finetuned-the-stack-bash
```

AdnanRiaz107 commited on Dec 6, 2023

Commit

d783450

1 Parent(s): f855c36

Training in progress, step 6500

Browse files

Files changed (2) hide show

adapter_model.safetensors +1 -1
runs/Dec06_14-17-17_2f8c0074e6bd/events.out.tfevents.1701872399.2f8c0074e6bd.175.0 +2 -2

adapter_model.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:1f88b5eaa69e7190dc4f51f09e6ac47db9cfcef27ce0bf38fe08a8883d4656f6
 size 3549272

 version https://git-lfs.github.com/spec/v1
+oid sha256:41a9b1b16bf9a902ffda93e85ab838ad67dfebd57dd34cdeb0af37fb5c5df56d
 size 3549272

runs/Dec06_14-17-17_2f8c0074e6bd/events.out.tfevents.1701872399.2f8c0074e6bd.175.0 CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:f7ba3f15234c8633105e924c80565f6170c1c4acaa1d81588cc8d2d89b73d998
-size 101901

 version https://git-lfs.github.com/spec/v1
+oid sha256:4d2bef0c20bb261248799d45a2d7c2e2bb7128aa11d43af03a25deec17013c66
+size 110022