Instructions to use pfnet/plamo-13b-instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use pfnet/plamo-13b-instruct with Transformers:

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

pipe = pipeline("text-generation", model="pfnet/plamo-13b-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("pfnet/plamo-13b-instruct", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use pfnet/plamo-13b-instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "pfnet/plamo-13b-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": "pfnet/plamo-13b-instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/pfnet/plamo-13b-instruct

SGLang

How to use pfnet/plamo-13b-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 "pfnet/plamo-13b-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": "pfnet/plamo-13b-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 "pfnet/plamo-13b-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": "pfnet/plamo-13b-instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use pfnet/plamo-13b-instruct with Docker Model Runner:
```
docker model run hf.co/pfnet/plamo-13b-instruct
```

mitmul commited on Jan 23, 2024

Commit

28979cf

verified ·

1 Parent(s): 2de2f12

Add assistant role

Browse files

Files changed (1) hide show

tokenizer_config.json +1 -1

tokenizer_config.json CHANGED Viewed

@@ -75,7 +75,7 @@
         ]
     },
     "bos_token": "<s>",
-    "chat_template": "{{ '以下はタスクを説明する指示で、文脈を説明した入力とペアになっています。要求を適切に補完するよう応答を書いてください。' }}\n\n{% for message in messages %}\n{% if message['role'] == 'user' %}\n{{ '### 指示:\n' + message['content'].strip() }}\n\n{% endif %}\n{% endfor %}\n{{ '### 応答:' }}",
     "clean_up_tokenization_spaces": false,
     "cls_token": "<cls>",
     "eos_token": "</s>",

         ]
     },
     "bos_token": "<s>",
+    "chat_template": "{{ '以下はタスクを説明する指示で、文脈を説明した入力とペアになっています。要求を適切に補完するよう応答を書いてください。\n\n' }}{% for message in messages %}{% if message['role'] == 'user' %}{{ '### 指示:\n' + message['content'].strip() + '\n\n' }}{% elif message['role'] == 'assistant' %}{{ '### 入力:\n' + message['content'].strip() + '\n\n' }}{% endif %}{% endfor %}{{ '### 応答:' }}",
     "clean_up_tokenization_spaces": false,
     "cls_token": "<cls>",
     "eos_token": "</s>",