Instructions to use Open4bits/LFM2.5-1.2B-Base-Quantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Open4bits/LFM2.5-1.2B-Base-Quantized with Transformers:

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

pipe = pipeline("text-generation", model="Open4bits/LFM2.5-1.2B-Base-Quantized")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Open4bits/LFM2.5-1.2B-Base-Quantized", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Open4bits/LFM2.5-1.2B-Base-Quantized with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Open4bits/LFM2.5-1.2B-Base-Quantized"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Open4bits/LFM2.5-1.2B-Base-Quantized",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Open4bits/LFM2.5-1.2B-Base-Quantized

SGLang

How to use Open4bits/LFM2.5-1.2B-Base-Quantized 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 "Open4bits/LFM2.5-1.2B-Base-Quantized" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Open4bits/LFM2.5-1.2B-Base-Quantized",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "Open4bits/LFM2.5-1.2B-Base-Quantized" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Open4bits/LFM2.5-1.2B-Base-Quantized",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Open4bits/LFM2.5-1.2B-Base-Quantized with Docker Model Runner:
```
docker model run hf.co/Open4bits/LFM2.5-1.2B-Base-Quantized
```

LFM2.5-1.2B-Base-Quantized / fp8 /chat_template.jinja

fmasterpro27

Add FP8 baseline

dca6c27 verified 4 months ago

raw

history blame contribute delete

1.3 kB

	{{- bos_token -}}{%- set system_prompt = "" -%}{%- set ns = namespace(system_prompt="") -%}{%- if messages[0]["role"] == "system" -%} {%- set ns.system_prompt = messages[0]["content"] -%} {%- set messages = messages[1:] -%}{%- endif -%}{%- if tools -%} {%- set ns.system_prompt = ns.system_prompt + ("
	" if ns.system_prompt else "") + "List of tools: <\|tool_list_start\|>[" -%} {%- for tool in tools -%} {%- if tool is not string -%} {%- set tool = tool \| tojson -%} {%- endif -%} {%- set ns.system_prompt = ns.system_prompt + tool -%} {%- if not loop.last -%} {%- set ns.system_prompt = ns.system_prompt + ", " -%} {%- endif -%} {%- endfor -%} {%- set ns.system_prompt = ns.system_prompt + "]<\|tool_list_end\|>" -%}{%- endif -%}{%- if ns.system_prompt -%} {{- "<\|im_start\|>system
	" + ns.system_prompt + "<\|im_end\|>
	" -}}{%- endif -%}{%- for message in messages -%} {{- "<\|im_start\|>" + message["role"] + "
	" -}} {%- set content = message["content"] -%} {%- if content is not string -%} {%- set content = content \| tojson -%} {%- endif -%} {%- if message["role"] == "tool" -%} {%- set content = "<\|tool_response_start\|>" + content + "<\|tool_response_end\|>" -%} {%- endif -%} {{- content + "<\|im_end\|>
	" -}}{%- endfor -%}{%- if add_generation_prompt -%} {{- "<\|im_start\|>assistant
	" -}}{%- endif -%}

	{{- bos_token -}}{%- set system_prompt = "" -%}{%- set ns = namespace(system_prompt="") -%}{%- if messages[0]["role"] == "system" -%} {%- set ns.system_prompt = messages[0]["content"] -%} {%- set messages = messages[1:] -%}{%- endif -%}{%- if tools -%} {%- set ns.system_prompt = ns.system_prompt + ("
	" if ns.system_prompt else "") + "List of tools: <\|tool_list_start\|>[" -%} {%- for tool in tools -%} {%- if tool is not string -%} {%- set tool = tool \| tojson -%} {%- endif -%} {%- set ns.system_prompt = ns.system_prompt + tool -%} {%- if not loop.last -%} {%- set ns.system_prompt = ns.system_prompt + ", " -%} {%- endif -%} {%- endfor -%} {%- set ns.system_prompt = ns.system_prompt + "]<\|tool_list_end\|>" -%}{%- endif -%}{%- if ns.system_prompt -%} {{- "<\|im_start\|>system
	" + ns.system_prompt + "<\|im_end\|>
	" -}}{%- endif -%}{%- for message in messages -%} {{- "<\|im_start\|>" + message["role"] + "
	" -}} {%- set content = message["content"] -%} {%- if content is not string -%} {%- set content = content \| tojson -%} {%- endif -%} {%- if message["role"] == "tool" -%} {%- set content = "<\|tool_response_start\|>" + content + "<\|tool_response_end\|>" -%} {%- endif -%} {{- content + "<\|im_end\|>
	" -}}{%- endfor -%}{%- if add_generation_prompt -%} {{- "<\|im_start\|>assistant
	" -}}{%- endif -%}