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

Libraries

How to use CSgaoshouGroup/CSCupcakeCoder with Transformers:

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

pipe = pipeline("text-generation", model="CSgaoshouGroup/CSCupcakeCoder")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("CSgaoshouGroup/CSCupcakeCoder")
model = AutoModelForCausalLM.from_pretrained("CSgaoshouGroup/CSCupcakeCoder")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use CSgaoshouGroup/CSCupcakeCoder with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/CSgaoshouGroup/CSCupcakeCoder

SGLang

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

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

wxk123 commited on Sep 16, 2024

Commit

f710253

verified ·

1 Parent(s): 00d9b9c

Upload config.json with huggingface_hub

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config.json +30 -0

config.json ADDED Viewed

	@@ -0,0 +1,30 @@

+{
+  "_name_or_path": "bigcode/starcoder2-3b",
+  "architectures": [
+    "Starcoder2ForCausalLM"
+  ],
+  "attention_dropout": 0.1,
+  "bos_token_id": 0,
+  "embedding_dropout": 0.1,
+  "eos_token_id": 0,
+  "hidden_act": "gelu_pytorch_tanh",
+  "hidden_size": 3072,
+  "initializer_range": 0.018042,
+  "intermediate_size": 12288,
+  "max_position_embeddings": 16384,
+  "mlp_type": "default",
+  "model_type": "starcoder2",
+  "norm_epsilon": 1e-05,
+  "norm_type": "layer_norm",
+  "num_attention_heads": 24,
+  "num_hidden_layers": 30,
+  "num_key_value_heads": 2,
+  "residual_dropout": 0.1,
+  "rope_theta": 999999.4420358813,
+  "sliding_window": 4096,
+  "torch_dtype": "float32",
+  "transformers_version": "4.44.2",
+  "use_bias": true,
+  "use_cache": true,
+  "vocab_size": 49152
+}