Instructions to use Undi95/ReMM-SLERP-L2-13B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Undi95/ReMM-SLERP-L2-13B with Transformers:

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

pipe = pipeline("text-generation", model="Undi95/ReMM-SLERP-L2-13B")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Undi95/ReMM-SLERP-L2-13B")
model = AutoModelForCausalLM.from_pretrained("Undi95/ReMM-SLERP-L2-13B")

Inference
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Undi95/ReMM-SLERP-L2-13B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Undi95/ReMM-SLERP-L2-13B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Undi95/ReMM-SLERP-L2-13B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Undi95/ReMM-SLERP-L2-13B

SGLang

How to use Undi95/ReMM-SLERP-L2-13B 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 "Undi95/ReMM-SLERP-L2-13B" \
    --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": "Undi95/ReMM-SLERP-L2-13B",
		"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 "Undi95/ReMM-SLERP-L2-13B" \
        --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": "Undi95/ReMM-SLERP-L2-13B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Undi95/ReMM-SLERP-L2-13B with Docker Model Runner:
```
docker model run hf.co/Undi95/ReMM-SLERP-L2-13B
```

Thanks for all your models over the years Undi95

by BingoBird - opened 29 days ago

Discussion

BingoBird

29 days ago

Really enjoyed learning from your work. +1

Take care of yourself. Be healthy; stay wary.

Skydea

29 days ago

Totally agree, love the Stuff Undi and IkariDev did with "NeverSleep" and their Models, gosh, an gemma 4 or other modern MOE with their stuff would be amazing.

xxx777xxxASD

25 days ago

Agree with agreement, they carried local roleplay on their shoulders for so much time that it's impossible to not be grateful. Undi, NeverSleep team, just thank you guys for everything

010O11

25 days ago

Sure, even nobody like me feel the duty, thank you @Undi95 for all the RP models!

Undi95

Owner 12 days ago

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