Instructions to use lmms-lab/llama3-llava-next-8b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use lmms-lab/llama3-llava-next-8b with Transformers:

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

pipe = pipeline("text-generation", model="lmms-lab/llama3-llava-next-8b")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoProcessor, AutoModelForCausalLM

processor = AutoProcessor.from_pretrained("lmms-lab/llama3-llava-next-8b")
model = AutoModelForCausalLM.from_pretrained("lmms-lab/llama3-llava-next-8b", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
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 lmms-lab/llama3-llava-next-8b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "lmms-lab/llama3-llava-next-8b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "lmms-lab/llama3-llava-next-8b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/lmms-lab/llama3-llava-next-8b

SGLang

How to use lmms-lab/llama3-llava-next-8b 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 "lmms-lab/llama3-llava-next-8b" \
    --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": "lmms-lab/llama3-llava-next-8b",
		"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 "lmms-lab/llama3-llava-next-8b" \
        --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": "lmms-lab/llama3-llava-next-8b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use lmms-lab/llama3-llava-next-8b with Docker Model Runner:
```
docker model run hf.co/lmms-lab/llama3-llava-next-8b
```

kcz358 commited on Aug 17, 2024

Commit

6d6dcb8

verified ·

1 Parent(s): e7e6a9f

Upload tokenizer

Browse files

Files changed (3) hide show

README.md +0 -2
tokenizer.json +10 -0
tokenizer_config.json +8 -0

README.md CHANGED Viewed

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-# Doc / guide: https://huggingface.co/docs/hub/model-cards
 {}
 ---

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 {}
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tokenizer.json CHANGED Viewed

@@ -2306,6 +2306,15 @@
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@@ -2348,6 +2357,7 @@
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     "byte_fallback": false,
     "vocab": {
       "!": 0,
       "\"": 1,

       "rstrip": false,
       "normalized": false,
       "special": true
+    },
+    {
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     }
   ],
   "normalizer": null,
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     "fuse_unk": false,
     "byte_fallback": false,
+    "ignore_merges": false,
     "vocab": {
       "!": 0,
       "\"": 1,

tokenizer_config.json CHANGED Viewed

@@ -2047,6 +2047,14 @@
       "rstrip": false,
       "single_word": false,
       "special": true
     }
   },
   "bos_token": "<|begin_of_text|>",

       "rstrip": false,
       "single_word": false,
       "special": true
+    },
+    "128256": {
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+      "lstrip": false,
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+      "single_word": false,
+      "special": true
     }
   },
   "bos_token": "<|begin_of_text|>",