Instructions to use Snowflake/snowflake-arctic-instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Snowflake/snowflake-arctic-instruct with Transformers:

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

pipe = pipeline("text-generation", model="Snowflake/snowflake-arctic-instruct", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("Snowflake/snowflake-arctic-instruct", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Snowflake/snowflake-arctic-instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Snowflake/snowflake-arctic-instruct"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Snowflake/snowflake-arctic-instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Snowflake/snowflake-arctic-instruct

SGLang

How to use Snowflake/snowflake-arctic-instruct 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 "Snowflake/snowflake-arctic-instruct" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Snowflake/snowflake-arctic-instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "Snowflake/snowflake-arctic-instruct" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Snowflake/snowflake-arctic-instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Snowflake/snowflake-arctic-instruct with Docker Model Runner:
```
docker model run hf.co/Snowflake/snowflake-arctic-instruct
```

jeffra commited on Apr 21, 2024

Commit

a47a33d

verified ·

1 Parent(s): 1f9a0a0

Create config.json

Browse files

Files changed (1) hide show

config.json +37 -0

config.json ADDED Viewed

	@@ -0,0 +1,37 @@

+{
+  "architectures": [
+    "ArcticForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "enable_expert_tensor_parallelism": false,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 7168,
+  "initializer_range": 0.02,
+  "intermediate_size": 4864,
+  "max_position_embeddings": 4096,
+  "model_type": "yak",
+  "moe_eval_capacity_factor": 1,
+  "moe_expert_parallel_size": 8,
+  "moe_layer_frequency": 1,
+  "moe_min_capacity": 0,
+  "moe_token_dropping": true,
+  "moe_train_capacity_factor": 1,
+  "num_attention_heads": 56,
+  "num_experts_per_tok": 2,
+  "num_hidden_layers": 35,
+  "num_key_value_heads": 56,
+  "num_local_experts": 128,
+  "parallel_attn_mlp_res": true,
+  "quantization": null,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 1000000.0,
+  "router_aux_loss_coef": 0.001,
+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.40.0.dev0",
+  "use_cache": false,
+  "vocab_size": 32000
+}