Instructions to use 01-ai/Yi-Coder-1.5B-Chat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use 01-ai/Yi-Coder-1.5B-Chat with Transformers:

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

pipe = pipeline("text-generation", model="01-ai/Yi-Coder-1.5B-Chat")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("01-ai/Yi-Coder-1.5B-Chat")
model = AutoModelForCausalLM.from_pretrained("01-ai/Yi-Coder-1.5B-Chat")
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]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use 01-ai/Yi-Coder-1.5B-Chat with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "01-ai/Yi-Coder-1.5B-Chat"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "01-ai/Yi-Coder-1.5B-Chat",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/01-ai/Yi-Coder-1.5B-Chat

SGLang

How to use 01-ai/Yi-Coder-1.5B-Chat 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 "01-ai/Yi-Coder-1.5B-Chat" \
    --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": "01-ai/Yi-Coder-1.5B-Chat",
		"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 "01-ai/Yi-Coder-1.5B-Chat" \
        --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": "01-ai/Yi-Coder-1.5B-Chat",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use 01-ai/Yi-Coder-1.5B-Chat with Docker Model Runner:
```
docker model run hf.co/01-ai/Yi-Coder-1.5B-Chat
```

Missing Tokenizer.json

by tjake - opened Sep 7, 2024

Discussion

tjake

Sep 7, 2024

I manually used the one from non-chat model but should be here too

haijian06

Sep 8, 2024

Hi 👋@tjake, all the files for our base model are here: https://huggingface.co/01-ai/Yi-Coder-1.5B/tree/main

tjake

Sep 8, 2024

Yes that's what I used but my project depends on the tokenizer.json being checked in with each model.

Is there a reason you left it out? Would you mind adding it to the chat models?

haijian06

Sep 9, 2024

Hi 👋 Hello, the base model includes tokenizer.json for debugging convenience or special adjustments, while the chat model may only need tokenizer.model to improve loading and running efficiency. However, all 1.5B tokenizer.json files are the same. If your project needs it, you can download the 1.5B base tokenizer.json and add it to your project.

tjake changed discussion status to closed Sep 9, 2024

Upload images, audio, and videos by dragging in the text input, pasting, or clicking here.

Tap or paste here to upload images

· Sign up or log in to comment