Instructions to use NexaAI/Octopus-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use NexaAI/Octopus-v2 with Transformers:

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

pipe = pipeline("text-generation", model="NexaAI/Octopus-v2")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("NexaAI/Octopus-v2")
model = AutoModelForCausalLM.from_pretrained("NexaAI/Octopus-v2")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use NexaAI/Octopus-v2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "NexaAI/Octopus-v2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "NexaAI/Octopus-v2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/NexaAI/Octopus-v2

SGLang

How to use NexaAI/Octopus-v2 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 "NexaAI/Octopus-v2" \
    --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": "NexaAI/Octopus-v2",
		"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 "NexaAI/Octopus-v2" \
        --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": "NexaAI/Octopus-v2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use NexaAI/Octopus-v2 with Docker Model Runner:
```
docker model run hf.co/NexaAI/Octopus-v2
```

zackli4ai commited on May 9, 2024

Commit

63b697e

verified ·

1 Parent(s): 524fc80

Update added_tokens.json

Browse files

Files changed (1) hide show

added_tokens.json +9 -9

added_tokens.json CHANGED Viewed

@@ -1,5 +1,14 @@
 {
   "<nexa_0>": 256000,
   "<nexa_10>": 256010,
   "<nexa_11>": 256011,
   "<nexa_12>": 256012,
@@ -10,15 +19,6 @@
   "<nexa_17>": 256017,
   "<nexa_18>": 256018,
   "<nexa_19>": 256019,
-  "<nexa_1>": 256001,
   "<nexa_20>": 256020,
-  "<nexa_2>": 256002,
-  "<nexa_3>": 256003,
-  "<nexa_4>": 256004,
-  "<nexa_5>": 256005,
-  "<nexa_6>": 256006,
-  "<nexa_7>": 256007,
-  "<nexa_8>": 256008,
-  "<nexa_9>": 256009,
   "<nexa_end>": 256021
 }

 {
   "<nexa_0>": 256000,
+  "<nexa_1>": 256001,
+  "<nexa_2>": 256002,
+  "<nexa_3>": 256003,
+  "<nexa_4>": 256004,
+  "<nexa_5>": 256005,
+  "<nexa_6>": 256006,
+  "<nexa_7>": 256007,
+  "<nexa_8>": 256008,
+  "<nexa_9>": 256009,
   "<nexa_10>": 256010,
   "<nexa_11>": 256011,
   "<nexa_12>": 256012,
   "<nexa_17>": 256017,
   "<nexa_18>": 256018,
   "<nexa_19>": 256019,
   "<nexa_20>": 256020,
   "<nexa_end>": 256021
 }