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

Libraries

How to use LiquidAI/LFM2.5-1.2B-Thinking with Transformers:

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

pipe = pipeline("text-generation", model="LiquidAI/LFM2.5-1.2B-Thinking")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("LiquidAI/LFM2.5-1.2B-Thinking")
model = AutoModelForCausalLM.from_pretrained("LiquidAI/LFM2.5-1.2B-Thinking", 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 LiquidAI/LFM2.5-1.2B-Thinking with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "LiquidAI/LFM2.5-1.2B-Thinking"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "LiquidAI/LFM2.5-1.2B-Thinking",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/LiquidAI/LFM2.5-1.2B-Thinking

SGLang

How to use LiquidAI/LFM2.5-1.2B-Thinking 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 "LiquidAI/LFM2.5-1.2B-Thinking" \
    --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": "LiquidAI/LFM2.5-1.2B-Thinking",
		"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 "LiquidAI/LFM2.5-1.2B-Thinking" \
        --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": "LiquidAI/LFM2.5-1.2B-Thinking",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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

Fix chat template: render tool_calls history and add <think> handling

by Cloudbusting - opened 26 days ago

base: refs/heads/main

←

from: refs/pr/4

Discussion Files changed

+38

-3

Files changed (1) hide show

chat_template.jinja +38 -3

chat_template.jinja CHANGED Viewed

@@ -1,5 +1,27 @@
 {{- bos_token -}}
 {%- set keep_past_thinking = keep_past_thinking | default(false) -%}
 {%- set ns = namespace(system_prompt="") -%}
 {%- if messages[0]["role"] == "system" -%}
     {%- set ns.system_prompt = messages[0]["content"] -%}
@@ -22,15 +44,24 @@
     {{- "<|im_start|>system\n" + ns.system_prompt + "<|im_end|>\n" -}}
 {%- endif -%}
 {%- set ns.last_assistant_index = -1 -%}
 {%- for message in messages -%}
     {%- if message["role"] == "assistant" -%}
         {%- set ns.last_assistant_index = loop.index0 -%}
     {%- endif -%}
 {%- endfor -%}
 {%- for message in messages -%}
     {{- "<|im_start|>" + message["role"] + "\n" -}}
-    {%- set content = message["content"] -%}
-    {%- if content is not string -%}
         {%- set content = content | tojson -%}
     {%- endif -%}
     {%- if message["role"] == "assistant" and not keep_past_thinking and loop.index0 != ns.last_assistant_index -%}
@@ -38,7 +69,11 @@
             {%- set content = content.split("</think>")[-1] | trim -%}
         {%- endif -%}
     {%- endif -%}
-    {{- content + "<|im_end|>\n" -}}
 {%- endfor -%}
 {%- if add_generation_prompt -%}
     {{- "<|im_start|>assistant\n" -}}

 {{- bos_token -}}
 {%- set keep_past_thinking = keep_past_thinking | default(false) -%}
+{%- macro format_arg_value(arg_value) -%}
+    {%- if arg_value is string -%}
+        {{- "'" + arg_value + "'" -}}
+    {%- elif arg_value is mapping -%}
+        {{- arg_value | tojson -}}
+    {%- else -%}
+        {{- arg_value | string -}}
+    {%- endif -%}
+{%- endmacro -%}
+{%- macro render_tool_calls(tool_calls) -%}
+    {%- set tool_calls_ns = namespace(tool_calls=[]) -%}
+    {%- for tool_call in tool_calls -%}
+        {%- set func_name = tool_call["function"]["name"] -%}
+        {%- set func_args = tool_call["function"]["arguments"] -%}
+        {%- set args_ns = namespace(arg_strings=[]) -%}
+        {%- for arg_name, arg_value in func_args.items() -%}
+            {%- set args_ns.arg_strings = args_ns.arg_strings + [arg_name + "=" + format_arg_value(arg_value)] -%}
+        {%- endfor -%}
+        {%- set tool_calls_ns.tool_calls = tool_calls_ns.tool_calls + [func_name + "(" + (args_ns.arg_strings | join(", ")) + ")"] -%}
+    {%- endfor -%}
+    {{- "<|tool_call_start|>[" + (tool_calls_ns.tool_calls | join(", ")) + "]<|tool_call_end|>" -}}
+{%- endmacro -%}
 {%- set ns = namespace(system_prompt="") -%}
 {%- if messages[0]["role"] == "system" -%}
     {%- set ns.system_prompt = messages[0]["content"] -%}
     {{- "<|im_start|>system\n" + ns.system_prompt + "<|im_end|>\n" -}}
 {%- endif -%}
 {%- set ns.last_assistant_index = -1 -%}
+{%- set ns.last_user_index = -1 -%}
 {%- for message in messages -%}
     {%- if message["role"] == "assistant" -%}
         {%- set ns.last_assistant_index = loop.index0 -%}
     {%- endif -%}
+    {%- if message["role"] == "user" -%}
+        {%- set ns.last_user_index = loop.index0 -%}
+    {%- endif -%}
 {%- endfor -%}
 {%- for message in messages -%}
     {{- "<|im_start|>" + message["role"] + "\n" -}}
+    {%- if message["role"] == "assistant" and message.get("thinking") and (keep_past_thinking or loop.index0 > ns.last_user_index) -%}
+        {{- "<think>" + message["thinking"] + "</think>" -}}
+    {%- endif -%}
+    {%- set content = message.get("content") -%}
+    {%- if not content -%}
+        {%- set content = "" -%}
+    {%- elif content is not string -%}
         {%- set content = content | tojson -%}
     {%- endif -%}
     {%- if message["role"] == "assistant" and not keep_past_thinking and loop.index0 != ns.last_assistant_index -%}
             {%- set content = content.split("</think>")[-1] | trim -%}
         {%- endif -%}
     {%- endif -%}
+    {{- content -}}
+    {%- if message["role"] == "assistant" and message.get("tool_calls") -%}
+        {{- render_tool_calls(message["tool_calls"]) -}}
+    {%- endif -%}
+    {{- "<|im_end|>\n" -}}
 {%- endfor -%}
 {%- if add_generation_prompt -%}
     {{- "<|im_start|>assistant\n" -}}