Instructions to use 01-ai/Yi-1.5-34B-Chat-16K 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-16K 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-16K")
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-16K")
model = AutoModelForCausalLM.from_pretrained("01-ai/Yi-1.5-34B-Chat-16K", 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-16K 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-16K"
# 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-16K",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/01-ai/Yi-1.5-34B-Chat-16K

SGLang

How to use 01-ai/Yi-1.5-34B-Chat-16K 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-16K" \
    --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-16K",
		"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-16K" \
        --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-16K",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use 01-ai/Yi-1.5-34B-Chat-16K with Docker Model Runner:
```
docker model run hf.co/01-ai/Yi-1.5-34B-Chat-16K
```

I'm confusing if this Chat model use the standard CHATML template? Is the bos_token <|im_start|> or <|startoftext|>? Is the eos_token <|im_end|> or <|endoftext|>?

by songkq - opened May 23, 2024

Discussion

songkq

May 23, 2024

•

edited May 23, 2024

As shown in Yi-1.5-34B-Chat-16K/config.json：
"bos_token_id": 1,
"eos_token_id": 2,

As shown in Yi-1.5-34B-Chat-16K/tokenizer_config.json：
"bos_token": "<|startoftext|>",
"eos_token": "<|im_end|>",

"1": {
"content": "<|startoftext|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"2": {
"content": "<|endoftext|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"7": {
"content": "<|im_end|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
}

lorinma

01-ai org Jun 12, 2024

My apologies for the late reply, we've updated the tokenizer.json, did that resolve your issue?
thanks!

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