Instructions to use TeeA/codeLlama_text2sql_word_r4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TeeA/codeLlama_text2sql_word_r4 with Transformers:

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

pipe = pipeline("text-generation", model="TeeA/codeLlama_text2sql_word_r4")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("TeeA/codeLlama_text2sql_word_r4")
model = AutoModelForCausalLM.from_pretrained("TeeA/codeLlama_text2sql_word_r4")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use TeeA/codeLlama_text2sql_word_r4 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "TeeA/codeLlama_text2sql_word_r4"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "TeeA/codeLlama_text2sql_word_r4",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/TeeA/codeLlama_text2sql_word_r4

SGLang

How to use TeeA/codeLlama_text2sql_word_r4 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 "TeeA/codeLlama_text2sql_word_r4" \
    --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": "TeeA/codeLlama_text2sql_word_r4",
		"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 "TeeA/codeLlama_text2sql_word_r4" \
        --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": "TeeA/codeLlama_text2sql_word_r4",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use TeeA/codeLlama_text2sql_word_r4 with Docker Model Runner:
```
docker model run hf.co/TeeA/codeLlama_text2sql_word_r4
```

TeeA commited on Apr 15, 2024

Commit

f38eae5

verified ·

1 Parent(s): 1d51c8d

Training in progress, step 200

Browse files

Files changed (4) hide show

adapter_config.json +32 -0
adapter_model.safetensors +3 -0
runs/Apr15_11-40-24_kao-dgxa-e10-u17/events.out.tfevents.1713177726.kao-dgxa-e10-u17.2134547.0 +3 -0
training_args.bin +3 -0

adapter_config.json ADDED Viewed

	@@ -0,0 +1,32 @@

+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "codellama/CodeLlama-7b-Instruct-hf",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 256,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 4,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "down_proj",
+    "gate_proj",
+    "k_proj",
+    "up_proj",
+    "q_proj",
+    "v_proj",
+    "o_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_rslora": false
+}

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