Instructions to use ByteForge/Defog_llama-3-sqlcoder-8b-ct2-int8_float16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ByteForge/Defog_llama-3-sqlcoder-8b-ct2-int8_float16 with Transformers:

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

pipe = pipeline("text-generation", model="ByteForge/Defog_llama-3-sqlcoder-8b-ct2-int8_float16")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("ByteForge/Defog_llama-3-sqlcoder-8b-ct2-int8_float16", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use ByteForge/Defog_llama-3-sqlcoder-8b-ct2-int8_float16 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ByteForge/Defog_llama-3-sqlcoder-8b-ct2-int8_float16"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ByteForge/Defog_llama-3-sqlcoder-8b-ct2-int8_float16",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/ByteForge/Defog_llama-3-sqlcoder-8b-ct2-int8_float16

SGLang

How to use ByteForge/Defog_llama-3-sqlcoder-8b-ct2-int8_float16 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 "ByteForge/Defog_llama-3-sqlcoder-8b-ct2-int8_float16" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ByteForge/Defog_llama-3-sqlcoder-8b-ct2-int8_float16",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "ByteForge/Defog_llama-3-sqlcoder-8b-ct2-int8_float16" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ByteForge/Defog_llama-3-sqlcoder-8b-ct2-int8_float16",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use ByteForge/Defog_llama-3-sqlcoder-8b-ct2-int8_float16 with Docker Model Runner:
```
docker model run hf.co/ByteForge/Defog_llama-3-sqlcoder-8b-ct2-int8_float16
```

Sagarkrishna commited on Jun 22, 2024

Commit

c89478f

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1 Parent(s): f60c100

Update README.md

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README.md CHANGED Viewed

@@ -18,13 +18,13 @@ Model type: [Text to SQL]
 License: [CC-by-SA-4.0]
 Finetuned from model: [Meta-Llama-3-8B-Instruct]
-## meta-llama/Meta-Llama-3-8B-Instruct for CTranslate2
 **The model is quantized version of the [defog/llama-3-sqlcoder-8b](https://huggingface.co/defog/llama-3-sqlcoder-8b) with int8_float16 quantization and can be used in [CTranslate2](https://github.com/OpenNMT/CTranslate2).**
 ## Conversion details
-The original model was converted on 2024-4 with the following command:
 ```
 ct2-transformers-converter --model Path\To\Local\meta-llama\Meta-Llama-3-8B-Instruct \
     --quantization int8_float16 --output_dir Meta-Llama-3-8B-Instruct-ct2-int8_float16

 License: [CC-by-SA-4.0]
 Finetuned from model: [Meta-Llama-3-8B-Instruct]
+## defog/llama-3-sqlcoder-8b for CTranslate2
 **The model is quantized version of the [defog/llama-3-sqlcoder-8b](https://huggingface.co/defog/llama-3-sqlcoder-8b) with int8_float16 quantization and can be used in [CTranslate2](https://github.com/OpenNMT/CTranslate2).**
 ## Conversion details
+The original model was converted on 2024-06 with the following command:
 ```
 ct2-transformers-converter --model Path\To\Local\meta-llama\Meta-Llama-3-8B-Instruct \
     --quantization int8_float16 --output_dir Meta-Llama-3-8B-Instruct-ct2-int8_float16