Instructions to use k4ran909/Fluxnat-Coder-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use k4ran909/Fluxnat-Coder-3B with Transformers:

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

pipe = pipeline("text-generation", model="k4ran909/Fluxnat-Coder-3B", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("k4ran909/Fluxnat-Coder-3B", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use k4ran909/Fluxnat-Coder-3B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "k4ran909/Fluxnat-Coder-3B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "k4ran909/Fluxnat-Coder-3B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/k4ran909/Fluxnat-Coder-3B

SGLang

How to use k4ran909/Fluxnat-Coder-3B 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 "k4ran909/Fluxnat-Coder-3B" \
    --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": "k4ran909/Fluxnat-Coder-3B",
		"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 "k4ran909/Fluxnat-Coder-3B" \
        --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": "k4ran909/Fluxnat-Coder-3B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Unsloth Desktop
Docker Model Runner
How to use k4ran909/Fluxnat-Coder-3B with Docker Model Runner:
```
docker model run hf.co/k4ran909/Fluxnat-Coder-3B
```

Fluxnat-Coder-3B / generation_config.json

k4ran909

Update v0.3.0 Fluxnat architecture config, tokenizer config, and model card

c46cd9c verified 14 days ago

Raw History Blame Contribute Delete

691 Bytes

{
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "max_length": 32768,
  "pad_token_id": 151665,
  "repetition_penalty": 1.05,
  "temperature": 0.7,
  "top_k": 20,
  "top_p": 0.8,
  "transformers_version": "5.5.0",
  "bad_words_ids": [
    [
      54364
    ],
    [
      1207,
      16948
    ],
    [
      48,
      16948
    ],
    [
      80,
      16948
    ],
    [
      2804,
      16948
    ],
    [
      2101,
      28260
    ],
    [
      452,
      28260
    ],
    [
      278,
      28260
    ],
    [
      48,
      54,
      953
    ],
    [
      969,
      3256,
      56550
    ]
  ],
  "model_name": "Fluxnat-Coder-3B",
  "author": "Fluxnat"
}

	{
	"do_sample": true,
	"eos_token_id": [
	151645,
	151643
	],
	"max_length": 32768,
	"pad_token_id": 151665,
	"repetition_penalty": 1.05,
	"temperature": 0.7,
	"top_k": 20,
	"top_p": 0.8,
	"transformers_version": "5.5.0",
	"bad_words_ids": [
	[
	54364
	],
	[
	1207,
	16948
	],
	[
	48,
	16948
	],
	[
	80,
	16948
	],
	[
	2804,
	16948
	],
	[
	2101,
	28260
	],
	[
	452,
	28260
	],
	[
	278,
	28260
	],
	[
	48,
	54,
	953
	],
	[
	969,
	3256,
	56550
	]
	],
	"model_name": "Fluxnat-Coder-3B",
	"author": "Fluxnat"
	}