Instructions to use saishf/Merge-Mayhem-L3-V2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use saishf/Merge-Mayhem-L3-V2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="saishf/Merge-Mayhem-L3-V2") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("saishf/Merge-Mayhem-L3-V2") model = AutoModelForCausalLM.from_pretrained("saishf/Merge-Mayhem-L3-V2") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Inference
- Local Apps Settings
- vLLM
How to use saishf/Merge-Mayhem-L3-V2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "saishf/Merge-Mayhem-L3-V2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "saishf/Merge-Mayhem-L3-V2", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/saishf/Merge-Mayhem-L3-V2
- SGLang
How to use saishf/Merge-Mayhem-L3-V2 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 "saishf/Merge-Mayhem-L3-V2" \ --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": "saishf/Merge-Mayhem-L3-V2", "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 "saishf/Merge-Mayhem-L3-V2" \ --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": "saishf/Merge-Mayhem-L3-V2", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use saishf/Merge-Mayhem-L3-V2 with Docker Model Runner:
docker model run hf.co/saishf/Merge-Mayhem-L3-V2
Quants
mradermacher has kindly provided quants here: mradermacher/Merge-Mayhem-L3-V2-GGUF
merge
This is a merge of pre-trained language models created using mergekit.
Merge Details
This is quite an interesting model, it's fun so far. But quite harsh, so if that's something you don't like, this model isn't for you :3
it's an attempt at loosely recreating ResplendentAI/SOVL_Llama3_8B but trying to keep it smarter, with the lovely openlynn/Llama-3-Soliloquy-8B-v2 holding it together. I'm personally enjoying this model, it's different from most llama-3 models.
Merge Method
This model was merged using the Model Stock merge method using openlynn/Llama-3-Soliloquy-8B-v2 as a base.
Models Merged
The following models were included in the merge:
- Undi95/Meta-Llama-3-8B-Instruct-hf + ResplendentAI/RP_Format_QuoteAsterisk_Llama3
- Undi95/Meta-Llama-3-8B-Instruct-hf + ResplendentAI/Smarts_Llama3
- Undi95/Meta-Llama-3-8B-Instruct-hf + ResplendentAI/Luna_Llama3
- Undi95/Meta-Llama-3-8B-Instruct-hf + ResplendentAI/BlueMoon_Llama3
- Undi95/Meta-Llama-3-8B-Instruct-hf + ResplendentAI/Aura_Llama3
Configuration
The following YAML configuration was used to produce this model:
models:
- model: Undi95/Meta-Llama-3-8B-Instruct-hf+ResplendentAI/Aura_Llama3
- model: Undi95/Meta-Llama-3-8B-Instruct-hf+ResplendentAI/Smarts_Llama3
- model: Undi95/Meta-Llama-3-8B-Instruct-hf+ResplendentAI/Luna_Llama3
- model: Undi95/Meta-Llama-3-8B-Instruct-hf+ResplendentAI/BlueMoon_Llama3
- model: Undi95/Meta-Llama-3-8B-Instruct-hf+ResplendentAI/RP_Format_QuoteAsterisk_Llama3
merge_method: model_stock
base_model: openlynn/Llama-3-Soliloquy-8B-v2
dtype: float16
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