Instructions to use support-pvelocity/Code-Llama-2-7B-instruct-text2sql with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use support-pvelocity/Code-Llama-2-7B-instruct-text2sql with Transformers:

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

pipe = pipeline("text-generation", model="support-pvelocity/Code-Llama-2-7B-instruct-text2sql")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("support-pvelocity/Code-Llama-2-7B-instruct-text2sql")
model = AutoModelForCausalLM.from_pretrained("support-pvelocity/Code-Llama-2-7B-instruct-text2sql", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use support-pvelocity/Code-Llama-2-7B-instruct-text2sql with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "support-pvelocity/Code-Llama-2-7B-instruct-text2sql"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "support-pvelocity/Code-Llama-2-7B-instruct-text2sql",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/support-pvelocity/Code-Llama-2-7B-instruct-text2sql

SGLang

How to use support-pvelocity/Code-Llama-2-7B-instruct-text2sql 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 "support-pvelocity/Code-Llama-2-7B-instruct-text2sql" \
    --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": "support-pvelocity/Code-Llama-2-7B-instruct-text2sql",
		"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 "support-pvelocity/Code-Llama-2-7B-instruct-text2sql" \
        --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": "support-pvelocity/Code-Llama-2-7B-instruct-text2sql",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use support-pvelocity/Code-Llama-2-7B-instruct-text2sql with Docker Model Runner:
```
docker model run hf.co/support-pvelocity/Code-Llama-2-7B-instruct-text2sql
```

support-pvelocity commited on Oct 25, 2023

Commit

6f2d199

1 Parent(s): 0cad57e

Upload LlamaForCausalLM

Browse files

Files changed (2) hide show

pytorch_model-00002-of-00002.bin +2 -2
pytorch_model.bin.index.json +1 -1

pytorch_model-00002-of-00002.bin CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:9fa969f0c0d9f03573aae774ca72a20b465abd9a612b1b53908af4a483203a89
-size 1619083442

 version https://git-lfs.github.com/spec/v1
+oid sha256:c4925d95daac9cfd10fc1fe2e714bbc211d099cacfc291e4ea20e96f855f8fb5
+size 3500443358

pytorch_model.bin.index.json CHANGED Viewed

@@ -1,6 +1,6 @@
 {
   "metadata": {
-    "total_size": 11981758464
   },
   "weight_map": {
     "lm_head.weight": "pytorch_model-00002-of-00002.bin",

 {
   "metadata": {
+    "total_size": 13477093376
   },
   "weight_map": {
     "lm_head.weight": "pytorch_model-00002-of-00002.bin",