Instructions to use LeoLM/leo-hessianai-7b-chat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use LeoLM/leo-hessianai-7b-chat with Transformers:

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

pipe = pipeline("text-generation", model="LeoLM/leo-hessianai-7b-chat", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("LeoLM/leo-hessianai-7b-chat", trust_remote_code=True)
model = AutoModelForMultimodalLM.from_pretrained("LeoLM/leo-hessianai-7b-chat", trust_remote_code=True)
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 LeoLM/leo-hessianai-7b-chat with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "LeoLM/leo-hessianai-7b-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": "LeoLM/leo-hessianai-7b-chat",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/LeoLM/leo-hessianai-7b-chat

SGLang

How to use LeoLM/leo-hessianai-7b-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 "LeoLM/leo-hessianai-7b-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": "LeoLM/leo-hessianai-7b-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 "LeoLM/leo-hessianai-7b-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": "LeoLM/leo-hessianai-7b-chat",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use LeoLM/leo-hessianai-7b-chat with Docker Model Runner:
```
docker model run hf.co/LeoLM/leo-hessianai-7b-chat
```

Porting model to ollama

by mars-ars - opened Feb 9, 2024

Discussion

mars-ars

Feb 9, 2024

Hi guys, I am trying to use the leo-hessianai-7B model on Ollama. I use the GGUF file (Q4_K_M.gguf from here https://huggingface.co/TheBloke/leo-hessianai-7B-GGUF/tree/main) and follow the instructions from Ollama (https://github.com/ollama/ollama/blob/main/docs/import.md). I already managed to generate answers with the model, but they are extremely wrong and hallucinating (you can say crazy). Unfortunately, I don't know what I'm doing wrong. I assume that the parameters or the template (in the Modelfile you have to create for Ollama) are incorrect.
Hope you can help me out 🙂

I tried the following Modelfiles:

FROM ./leo-hessianai-7b.Q4_K_M.gguf
TEMPLATE """{{- if .System }}
<|im_start|>system {{ .System }}<|im_end|>
{{- end }}
<|im_start|>user
{{ .Prompt }}<|im_end|>
<|im_start|>assistant
"""

SYSTEM """"""

PARAMETER stop <|im_start|>
PARAMETER stop <|im_end|>

FROM ./leo-hessianai-7b.Q4_K_M.gguf
TEMPLATE "[INST] {{ .Prompt }} [/INST]"

(The same problem occurred, when I used the safetensors from this repo and used the ollama tools to convert and quantize the model.)

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