Instructions to use defog/sqlcoder-7b-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use defog/sqlcoder-7b-2 with Transformers:

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

pipe = pipeline("text-generation", model="defog/sqlcoder-7b-2")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("defog/sqlcoder-7b-2")
model = AutoModelForCausalLM.from_pretrained("defog/sqlcoder-7b-2")

llama-cpp-python

How to use defog/sqlcoder-7b-2 with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="defog/sqlcoder-7b-2",
	filename="sqlcoder-7b-q5_k_m.gguf",
)

output = llm(
	"Once upon a time,",
	max_tokens=512,
	echo=True
)
print(output)

Inference
Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use defog/sqlcoder-7b-2 with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf defog/sqlcoder-7b-2:Q5_K_M
# Run inference directly in the terminal:
llama-cli -hf defog/sqlcoder-7b-2:Q5_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf defog/sqlcoder-7b-2:Q5_K_M
# Run inference directly in the terminal:
llama-cli -hf defog/sqlcoder-7b-2:Q5_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf defog/sqlcoder-7b-2:Q5_K_M
# Run inference directly in the terminal:
./llama-cli -hf defog/sqlcoder-7b-2:Q5_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf defog/sqlcoder-7b-2:Q5_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf defog/sqlcoder-7b-2:Q5_K_M

Use Docker

docker model run hf.co/defog/sqlcoder-7b-2:Q5_K_M

LM Studio
Jan

vLLM

How to use defog/sqlcoder-7b-2 with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/defog/sqlcoder-7b-2:Q5_K_M

SGLang

How to use defog/sqlcoder-7b-2 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 "defog/sqlcoder-7b-2" \
    --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": "defog/sqlcoder-7b-2",
		"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 "defog/sqlcoder-7b-2" \
        --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": "defog/sqlcoder-7b-2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Ollama
How to use defog/sqlcoder-7b-2 with Ollama:
```
ollama run hf.co/defog/sqlcoder-7b-2:Q5_K_M
```

Unsloth Studio new

How to use defog/sqlcoder-7b-2 with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for defog/sqlcoder-7b-2 to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for defog/sqlcoder-7b-2 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for defog/sqlcoder-7b-2 to start chatting

Docker Model Runner
How to use defog/sqlcoder-7b-2 with Docker Model Runner:
```
docker model run hf.co/defog/sqlcoder-7b-2:Q5_K_M
```

Lemonade

How to use defog/sqlcoder-7b-2 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull defog/sqlcoder-7b-2:Q5_K_M

Run and chat with the model

lemonade run user.sqlcoder-7b-2-Q5_K_M

List all available models

lemonade list

rishdotblog commited on Feb 5, 2024

Commit

6c347af

verified ·

1 Parent(s): b5ff6ca

Training in progress, step 100

Browse files

Files changed (6) hide show

config.json +28 -0
label_mask.npy +3 -0
labeled_matches.npy +3 -0
labels.npy +3 -0
predictions.npy +3 -0
training_args.bin +3 -0

config.json ADDED Viewed

	@@ -0,0 +1,28 @@

+{
+  "_name_or_path": "codellama/CodeLlama-7b-hf",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 11008,
+  "max_position_embeddings": 16384,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 32,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 1000000,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.37.2",
+  "use_cache": true,
+  "vocab_size": 32016
+}

label_mask.npy ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:ce06db10b5b506fcc10ada7fb9621e9a82a0b0560d04856e3571f432c3774fb9
+size 458228

labeled_matches.npy ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:5b5799634caa60d2e16cad19d605b9aaf72061133c60e0f18ac70454c9183c38
+size 458228

labels.npy ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:e598810721e5682a88d42fa5c4844c2f1fce92c41a2fb0da1b28fe1994b47cc9
+size 3664928

predictions.npy ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:4f5e5a69174d65589546b77c11d02df7e01fcdbe76c9ca71960acb0222f4477e
+size 3664928

training_args.bin ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:d76514892c133615428b3e93206e03f334310b47e0b9565e067a577f87a2f1b2
+size 4856