Instructions to use Repv1111/LFM2.5-VL-450M-Vebe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Repv1111/LFM2.5-VL-450M-Vebe with Transformers:

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

pipe = pipeline("image-text-to-text", model="Repv1111/LFM2.5-VL-450M-Vebe")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("Repv1111/LFM2.5-VL-450M-Vebe")
model = AutoModelForMultimodalLM.from_pretrained("Repv1111/LFM2.5-VL-450M-Vebe", device_map="auto")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
inputs = processor.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(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Repv1111/LFM2.5-VL-450M-Vebe with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Repv1111/LFM2.5-VL-450M-Vebe"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Repv1111/LFM2.5-VL-450M-Vebe",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/Repv1111/LFM2.5-VL-450M-Vebe

SGLang

How to use Repv1111/LFM2.5-VL-450M-Vebe 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 "Repv1111/LFM2.5-VL-450M-Vebe" \
    --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": "Repv1111/LFM2.5-VL-450M-Vebe",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

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 "Repv1111/LFM2.5-VL-450M-Vebe" \
        --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": "Repv1111/LFM2.5-VL-450M-Vebe",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Docker Model Runner
How to use Repv1111/LFM2.5-VL-450M-Vebe with Docker Model Runner:
```
docker model run hf.co/Repv1111/LFM2.5-VL-450M-Vebe
```

Repv1111 commited on Jun 25

Commit

f8da28f

verified ·

1 Parent(s): c42aedd

Upload tokenizer.json

Browse files

Files changed (1) hide show

tokenizer.json +7 -7

tokenizer.json CHANGED Viewed

@@ -32,11 +32,11 @@
     },
     {
       "id": 3,
-      "content": "<|fim_pre|>",
-      "single_word": false,
-      "lstrip": false,
-      "rstrip": false,
-      "normalized": false,
       "special": true
     },
     {
@@ -4676,7 +4676,7 @@
       "<|pad|>": 0,
       "<|startoftext|>": 1,
       "<|endoftext|>": 2,
-      "<|fim_pre|>": 3,
       "<|fim_mid|>": 4,
       "<|fim_suf|>": 5,
       "<|im_start|>": 6,
@@ -37895,7 +37895,7 @@
       "Como": 33219,
       "Ġbust": 33220,
       "Region": 33221,
-      "Help": 33222,
       "ĠÑĤÐµÐº": 33223,
       "mc": 33224,
       "Ġperceive": 33225,

     },
     {
       "id": 3,
+      "content": "<|aczsend_framework|>",
+      "single_word": true,
+      "lstrip": true,
+      "rstrip": true,
+      "normalized": true,
       "special": true
     },
     {
       "<|pad|>": 0,
       "<|startoftext|>": 1,
       "<|endoftext|>": 2,
+      "<|aczsend_framework|>": 3,
       "<|fim_mid|>": 4,
       "<|fim_suf|>": 5,
       "<|im_start|>": 6,
       "Como": 33219,
       "Ġbust": 33220,
       "Region": 33221,
+      "Vebe framework zend": 33222,
       "ĠÑĤÐµÐº": 33223,
       "mc": 33224,
       "Ġperceive": 33225,