Instructions to use impactframes/molmo-7B-O-bnb-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use impactframes/molmo-7B-O-bnb-4bit with Transformers:

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

pipe = pipeline("text-generation", model="impactframes/molmo-7B-O-bnb-4bit", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("impactframes/molmo-7B-O-bnb-4bit", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use impactframes/molmo-7B-O-bnb-4bit with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "impactframes/molmo-7B-O-bnb-4bit"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "impactframes/molmo-7B-O-bnb-4bit",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/impactframes/molmo-7B-O-bnb-4bit

SGLang

How to use impactframes/molmo-7B-O-bnb-4bit 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 "impactframes/molmo-7B-O-bnb-4bit" \
    --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": "impactframes/molmo-7B-O-bnb-4bit",
		"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 "impactframes/molmo-7B-O-bnb-4bit" \
        --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": "impactframes/molmo-7B-O-bnb-4bit",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use impactframes/molmo-7B-O-bnb-4bit with Docker Model Runner:
```
docker model run hf.co/impactframes/molmo-7B-O-bnb-4bit
```

molmo-7B-O-bnb-4bit / tokenizer_config.json

impactframes

Duplicate from cyan2k/molmo-7B-O-bnb-4bit

c712a26 verified over 1 year ago

raw

history blame contribute delete

5.9 kB

	{
	"add_prefix_space": false,
	"added_tokens_decoder": {
	"100256": {
	"content": "<\|extra_id_0\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"100257": {
	"content": "<\|endoftext\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"100258": {
	"content": "<\|fim_prefix\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"100259": {
	"content": "<\|fim_middle\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"100260": {
	"content": "<\|fim_suffix\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"100261": {
	"content": "\|\|\|PHONE_NUMBER\|\|\|",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"100262": {
	"content": "\|\|\|EMAIL_ADDRESS\|\|\|",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"100263": {
	"content": "\|\|\|IP_ADDRESS\|\|\|",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"100264": {
	"content": "<\|im_start\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"100265": {
	"content": "<\|im_end\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"100266": {
	"content": "<\|extra_id_1\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"100267": {
	"content": "<\|extra_id_2\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"100268": {
	"content": "<\|extra_id_3\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"100269": {
	"content": "<\|extra_id_4\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"100270": {
	"content": "<\|extra_id_5\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"100271": {
	"content": "<\|extra_id_6\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"100272": {
	"content": "<\|extra_id_7\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"100273": {
	"content": "<\|extra_id_8\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"100274": {
	"content": "<\|extra_id_9\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"100275": {
	"content": "<\|extra_id_10\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"100276": {
	"content": "<\|endofprompt\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"100277": {
	"content": "<\|pad\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"100278": {
	"content": "<im_start>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"100279": {
	"content": "<im_end>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"100280": {
	"content": "<im_patch>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"100281": {
	"content": "<im_col>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"100282": {
	"content": "<\|image\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	}
	},
	"additional_special_tokens": [
	"<im_start>",
	"<im_end>",
	"<im_patch>",
	"<im_col>",
	"<\|image\|>"
	],
	"auto_map": {
	"AutoProcessor": "preprocessing_molmo.MolmoProcessor"
	},
	"bos_token": "<\|endoftext\|>",
	"chat_template": "{% for message in messages %}{{'<\|im_start\|>' + message['role'] + '\n' + message['content'] + '<\|im_end\|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<\|im_start\|>assistant\n' }}{% endif %}",
	"clean_up_tokenization_spaces": false,
	"eos_token": "<\|endoftext\|>",
	"model_max_length": 8192,
	"pad_token": "<\|pad\|>",
	"processor_class": "MolmoProcessor",
	"tokenizer_class": "GPT2Tokenizer",
	"torch_dtype": "auto",
	"unk_token": "<\|endoftext\|>"
	}