Instructions to use Rakhman16/program-synthesis-java-codet5-xlcost with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Rakhman16/program-synthesis-java-codet5-xlcost with Transformers:

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

pipe = pipeline("text-generation", model="Rakhman16/program-synthesis-java-codet5-xlcost")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("Rakhman16/program-synthesis-java-codet5-xlcost")
model = AutoModelForSeq2SeqLM.from_pretrained("Rakhman16/program-synthesis-java-codet5-xlcost", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Rakhman16/program-synthesis-java-codet5-xlcost with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Rakhman16/program-synthesis-java-codet5-xlcost"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Rakhman16/program-synthesis-java-codet5-xlcost",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Rakhman16/program-synthesis-java-codet5-xlcost

SGLang

How to use Rakhman16/program-synthesis-java-codet5-xlcost 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 "Rakhman16/program-synthesis-java-codet5-xlcost" \
    --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": "Rakhman16/program-synthesis-java-codet5-xlcost",
		"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 "Rakhman16/program-synthesis-java-codet5-xlcost" \
        --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": "Rakhman16/program-synthesis-java-codet5-xlcost",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Rakhman16/program-synthesis-java-codet5-xlcost with Docker Model Runner:
```
docker model run hf.co/Rakhman16/program-synthesis-java-codet5-xlcost
```

Rakhman16 commited on Dec 9, 2024

Commit

2f6177f

verified ·

1 Parent(s): c989f5d

Training in progress, step 2000

Browse files

Files changed (2) hide show

model.safetensors +1 -1
runs/Dec09_04-35-23_b8f63645e3b4/events.out.tfevents.1733718925.b8f63645e3b4.1257.0 +2 -2

model.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:9d7652a9232339d6e1ccab695f9ba6075718fdf1dba2b8c3ef19b0f3a6ee730a
 size 891558696

 version https://git-lfs.github.com/spec/v1
+oid sha256:b4976591835d5aca83e7b5f41a00cb52acee5cb572e72a643fb9be051e9f83d1
 size 891558696

runs/Dec09_04-35-23_b8f63645e3b4/events.out.tfevents.1733718925.b8f63645e3b4.1257.0 CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:f0e6877a7a9da28eb589b2ee06c04c0d39304568996f8aeedcbf23caa7e0bf30
-size 6904

 version https://git-lfs.github.com/spec/v1
+oid sha256:944451640697bb184a1c01f6d3e0b0ff0f4ac3023e228712f70a5681504fea16
+size 7115