Instructions to use RedHatAI/starcoder2-15b-quantized.w8a16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use RedHatAI/starcoder2-15b-quantized.w8a16 with Transformers:

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

pipe = pipeline("text-generation", model="RedHatAI/starcoder2-15b-quantized.w8a16")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("RedHatAI/starcoder2-15b-quantized.w8a16")
model = AutoModelForCausalLM.from_pretrained("RedHatAI/starcoder2-15b-quantized.w8a16")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use RedHatAI/starcoder2-15b-quantized.w8a16 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "RedHatAI/starcoder2-15b-quantized.w8a16"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "RedHatAI/starcoder2-15b-quantized.w8a16",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/RedHatAI/starcoder2-15b-quantized.w8a16

SGLang

How to use RedHatAI/starcoder2-15b-quantized.w8a16 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 "RedHatAI/starcoder2-15b-quantized.w8a16" \
    --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": "RedHatAI/starcoder2-15b-quantized.w8a16",
		"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 "RedHatAI/starcoder2-15b-quantized.w8a16" \
        --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": "RedHatAI/starcoder2-15b-quantized.w8a16",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use RedHatAI/starcoder2-15b-quantized.w8a16 with Docker Model Runner:
```
docker model run hf.co/RedHatAI/starcoder2-15b-quantized.w8a16
```

mgoin commited on Oct 9, 2024

Commit

25ac565

verified ·

1 Parent(s): c21f287

Updated compression_config to quantization_config

Browse files

Files changed (1) hide show

config.json +25 -25

config.json CHANGED Viewed

@@ -5,7 +5,30 @@
   ],
   "attention_dropout": 0.1,
   "bos_token_id": 0,
-  "compression_config": {
     "config_groups": {
       "group_0": {
         "input_activations": null,
@@ -34,28 +57,5 @@
     "kv_cache_scheme": null,
     "quant_method": "compressed-tensors",
     "quantization_status": "frozen"
-  },
-  "embedding_dropout": 0.1,
-  "eos_token_id": 0,
-  "hidden_act": "gelu_pytorch_tanh",
-  "hidden_size": 6144,
-  "initializer_range": 0.01275,
-  "intermediate_size": 24576,
-  "max_position_embeddings": 16384,
-  "mlp_type": "default",
-  "model_type": "starcoder2",
-  "norm_epsilon": 1e-05,
-  "norm_type": "layer_norm",
-  "num_attention_heads": 48,
-  "num_hidden_layers": 40,
-  "num_key_value_heads": 4,
-  "residual_dropout": 0.1,
-  "rope_theta": 100000,
-  "sliding_window": 4096,
-  "tie_word_embeddings": false,
-  "torch_dtype": "float32",
-  "transformers_version": "4.43.3",
-  "use_bias": true,
-  "use_cache": true,
-  "vocab_size": 49152
 }

   ],
   "attention_dropout": 0.1,
   "bos_token_id": 0,
+  "embedding_dropout": 0.1,
+  "eos_token_id": 0,
+  "hidden_act": "gelu_pytorch_tanh",
+  "hidden_size": 6144,
+  "initializer_range": 0.01275,
+  "intermediate_size": 24576,
+  "max_position_embeddings": 16384,
+  "mlp_type": "default",
+  "model_type": "starcoder2",
+  "norm_epsilon": 1e-05,
+  "norm_type": "layer_norm",
+  "num_attention_heads": 48,
+  "num_hidden_layers": 40,
+  "num_key_value_heads": 4,
+  "residual_dropout": 0.1,
+  "rope_theta": 100000,
+  "sliding_window": 4096,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float32",
+  "transformers_version": "4.43.3",
+  "use_bias": true,
+  "use_cache": true,
+  "vocab_size": 49152,
+  "quantization_config": {
     "config_groups": {
       "group_0": {
         "input_activations": null,
     "kv_cache_scheme": null,
     "quant_method": "compressed-tensors",
     "quantization_status": "frozen"
+  }
 }