Instructions to use JetBrains/Mellum-4b-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use JetBrains/Mellum-4b-base with Transformers:

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

pipe = pipeline("text-generation", model="JetBrains/Mellum-4b-base")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("JetBrains/Mellum-4b-base")
model = AutoModelForCausalLM.from_pretrained("JetBrains/Mellum-4b-base")

Inference
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use JetBrains/Mellum-4b-base with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "JetBrains/Mellum-4b-base"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "JetBrains/Mellum-4b-base",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/JetBrains/Mellum-4b-base

SGLang

How to use JetBrains/Mellum-4b-base 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 "JetBrains/Mellum-4b-base" \
    --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": "JetBrains/Mellum-4b-base",
		"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 "JetBrains/Mellum-4b-base" \
        --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": "JetBrains/Mellum-4b-base",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use JetBrains/Mellum-4b-base with Docker Model Runner:
```
docker model run hf.co/JetBrains/Mellum-4b-base
```

Mellum-4b-base / tokenizer_config.json

ivandolgov

initial commit

9736cdc about 1 year ago

raw

history blame contribute delete

5.65 kB

	{
	"add_bos_token": false,
	"add_prefix_space": false,
	"added_tokens_decoder": {
	"0": {
	"content": "<\|endoftext\|>",
	"lstrip": false,
	"normalized": true,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"1": {
	"content": "<fim_prefix>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"2": {
	"content": "<fim_middle>",
	"lstrip": false,
	"normalized": false,
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	},
	"3": {
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	},
	"4": {
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	},
	"5": {
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	},
	"6": {
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	"9": {
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	"14": {
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	"15": {
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	},
	"16": {
	"content": "<commit_msg>",
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	"special": true
	},
	"17": {
	"content": "<commit_after>",
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	"normalized": false,
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	"single_word": false,
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	},
	"18": {
	"content": "<reponame>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"19": {
	"content": "<system>",
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	"special": true
	},
	"20": {
	"content": "</system>",
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	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"21": {
	"content": "<user>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"22": {
	"content": "</user>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"23": {
	"content": "<assistant>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"24": {
	"content": "</assistant>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"25": {
	"content": "<think>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"26": {
	"content": "</think>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	}
	},
	"additional_special_tokens": [
	"<gh_stars>",
	"</system>",
	"<issue_start>",
	"</think>",
	"<commit_after>",
	"<assistant>",
	"<jupyter_text>",
	"<fim_middle>",
	"</assistant>",
	"<jupyter_code>",
	"<user>",
	"<filename>",
	"<think>",
	"<fim_suffix>",
	"<fim_prefix>",
	"<commit_msg>",
	"<fim_pad>",
	"<system>",
	"<issue_comment>",
	"<reponame>",
	"<jupyter_start>",
	"<issue_closed>",
	"<commit_before>",
	"<empty_output>",
	"<jupyter_output>",
	"</user>"
	],
	"bos_token": "<\|endoftext\|>",
	"clean_up_tokenization_spaces": true,
	"eos_token": "<\|endoftext\|>",
	"errors": "replace",
	"extra_special_tokens": {},
	"model_max_length": 1000000000000000019884624838656,
	"pad_token": "<\|endoftext\|>",
	"tokenizer_class": "GPT2Tokenizer",
	"unk_token": "<\|endoftext\|>"
	}