Instructions to use netcat420/MFANN3bv0.20.17 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use netcat420/MFANN3bv0.20.17 with Transformers:

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

pipe = pipeline("text-generation", model="netcat420/MFANN3bv0.20.17")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("netcat420/MFANN3bv0.20.17")
model = AutoModelForCausalLM.from_pretrained("netcat420/MFANN3bv0.20.17", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use netcat420/MFANN3bv0.20.17 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "netcat420/MFANN3bv0.20.17"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "netcat420/MFANN3bv0.20.17",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/netcat420/MFANN3bv0.20.17

SGLang

How to use netcat420/MFANN3bv0.20.17 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 "netcat420/MFANN3bv0.20.17" \
    --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": "netcat420/MFANN3bv0.20.17",
		"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 "netcat420/MFANN3bv0.20.17" \
        --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": "netcat420/MFANN3bv0.20.17",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use netcat420/MFANN3bv0.20.17 with Docker Model Runner:
```
docker model run hf.co/netcat420/MFANN3bv0.20.17
```

system prompt: Instruct: {instruction} Output:

good training loss of 0.33 avg on the MFANN dataset! as of 9/20/24

this model is a general model trained to generate text on a vast array of tasks and will be the last pre release in the 3b branch before the first major release!

Downloads last month: 11

Safetensors

Model size

3B params

Tensor type

F32

Model tree for netcat420/MFANN3bv0.20.17

Base model

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Finetuned

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Merges

1 model

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Dataset used to train netcat420/MFANN3bv0.20.17