Instructions to use 01-ai/Yi-1.5-34B-Chat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use 01-ai/Yi-1.5-34B-Chat with Transformers:

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

pipe = pipeline("text-generation", model="01-ai/Yi-1.5-34B-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-1.5-34B-Chat")
model = AutoModelForCausalLM.from_pretrained("01-ai/Yi-1.5-34B-Chat", device_map="auto")
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 Settings

vLLM

How to use 01-ai/Yi-1.5-34B-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-1.5-34B-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-1.5-34B-Chat",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/01-ai/Yi-1.5-34B-Chat

SGLang

How to use 01-ai/Yi-1.5-34B-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-1.5-34B-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-1.5-34B-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-1.5-34B-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-1.5-34B-Chat",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use 01-ai/Yi-1.5-34B-Chat with Docker Model Runner:
```
docker model run hf.co/01-ai/Yi-1.5-34B-Chat
```

Update README.md

#17

by ReactionControl - opened Jan 22

base: refs/heads/main

←

from: refs/pr/17

Discussion Files changed

-2

ReactionControl

Jan 22

Hi there! I just wanted to say that your model is absolutely fantastic. We are interested in contributing to update the README of your model to include the base_model information. This is to help address the missing details in the model card. Thank you for your amazing work!

Update README.md793bbe6d

xujfcn

Feb 24

Great discussion! For anyone wanting to quickly test this, Crazyrouter offers API access to this model. No infrastructure setup needed — just an API key and the standard OpenAI SDK.

cherryyan

Aug 20

This is a great contribution to the README. Including base model information is super helpful for users. The Choicer Voicer

cherryyan

Aug 20

This is a great model, thanks for sharing the usage instructions! It's really helpful to see the different ways to integrate it. play the choicer voicer

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