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
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

Re:MythoMax (ReMM) is a recreation trial of the original MythoMax-L2-B13 with updated models.

This merge use SLERP [TESTING] to merge ReML and Huginn v1.2.

Command useds and explaination :

Due to hardware limitation, some merge was done in 2 part.

- Recreate ReML : Mythologic (v2) (Chronos/Hermes/Airboros)
=> Replacing Chronos by The-Face-Of-Goonery/Chronos-Beluga-v2-13bfp16 (0.30)
=> Replacing Airoboros by jondurbin/airoboros-l2-13b-2.1 (last version) (0.40)
=> Keeping NousResearch/Nous-Hermes-Llama2-13b (0.30)

Part 1: python ties_merge.py TheBloke/Llama-2-13B-fp16 ./ReML-L2-13B-part1  --merge The-Face-Of-Goonery/Chronos-Beluga-v2-13bfp16 --density 0.42 --merge jondurbin/airoboros-l2-13b-2.1 --density 0.56 --cuda

Part 2: python ties_merge.py TheBloke/Llama-2-13B-fp16 ./ReML-L2-13B --merge NousResearch/Nous-Hermes-Llama2-13b --density 0.30 --merge Undi95/ReML-L2-13B-part1 --density 0.70 --cuda

With that :
- Recreate ReMM : MythoMax (v2) (Mythologic/Huginn v1)
=> Replacing Mythologic by the one above (0.5)
=> Replacing Huginn by The-Face-Of-Goonery/Huginn-13b-v1.2 (hottest) (0.5)

Part 3: python slerpmergelm.py "The-Face-Of-Goonery_Huginn-13b-v1.2" "Undi95_ReML-L2-13B" "result"

Version of SLERP used is different to accept usage on notebook : https://github.com/Undi95/LLM-SLERP-MergeTest/tree/main (Thanks @Vali)

Description

This repo contains fp16 files of ReMM-SLERP, a recreation of the original MythoMax, but updated and merged with SLERP.

Models used

TheBloke/Llama-2-13B-fp16 (base)
The-Face-Of-Goonery/Chronos-Beluga-v2-13bfp16
jondurbin/airoboros-l2-13b-2.1
NousResearch/Nous-Hermes-Llama2-13b
The-Face-Of-Goonery/Huginn-13b-v1.2
ReML-L2-13B (Private recreation trial of an updated Mythologic-L2-13B)

Prompt template: Alpaca

Below is an instruction that describes a task. Write a response that appropriately completes the request.

### Instruction:
{prompt}

### Response:

Special thanks to Sushi kek

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	50.99
ARC (25-shot)	60.92
HellaSwag (10-shot)	83.56
MMLU (5-shot)	55.33
TruthfulQA (0-shot)	51.97
Winogrande (5-shot)	75.22
GSM8K (5-shot)	9.17
DROP (3-shot)	20.76

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Model tree for Undi95/ReMM-SLERP-L2-13B

Base model

NousResearch/Nous-Hermes-Llama2-13b

Finetuned

(5)

this model

Finetunes

1 model

Quantizations

5 models

Spaces using Undi95/ReMM-SLERP-L2-13B 46

Collection including Undi95/ReMM-SLERP-L2-13B

ReMM series

Collection

Models based on MythoMax with updated base models. • 4 items • Updated Oct 12, 2023 • 10