Text Generation
Transformers
Safetensors
English
mistral
Merge
mergekit
MTSAIR/multi_verse_model
rwitz/experiment26-truthy-iter-0
MaziyarPanahi/Calme-7B-Instruct-v0.2
chemistry
biology
math
Eval Results (legacy)
text-generation-inference
Instructions to use louisbrulenaudet/Maxine-7B-0401-stock with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use louisbrulenaudet/Maxine-7B-0401-stock with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="louisbrulenaudet/Maxine-7B-0401-stock")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("louisbrulenaudet/Maxine-7B-0401-stock") model = AutoModelForCausalLM.from_pretrained("louisbrulenaudet/Maxine-7B-0401-stock", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use louisbrulenaudet/Maxine-7B-0401-stock with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "louisbrulenaudet/Maxine-7B-0401-stock" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "louisbrulenaudet/Maxine-7B-0401-stock", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/louisbrulenaudet/Maxine-7B-0401-stock
- SGLang
How to use louisbrulenaudet/Maxine-7B-0401-stock 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 "louisbrulenaudet/Maxine-7B-0401-stock" \ --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": "louisbrulenaudet/Maxine-7B-0401-stock", "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 "louisbrulenaudet/Maxine-7B-0401-stock" \ --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": "louisbrulenaudet/Maxine-7B-0401-stock", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use louisbrulenaudet/Maxine-7B-0401-stock with Docker Model Runner:
docker model run hf.co/louisbrulenaudet/Maxine-7B-0401-stock

Maxine-7B-0401-stock, an xtraordinary 7B model
03-22-2024 - To date, louisbrulenaudet/Pearl-34B-ties is the "Best 🤝 base merges and moerges model of around 30B" on the Open LLM Leaderboard.
Configuration
models:
- model: OpenPipe/mistral-ft-optimized-1227
- model: MTSAIR/multi_verse_model
- model: rwitz/experiment26-truthy-iter-0
- model: MaziyarPanahi/Calme-7B-Instruct-v0.2
merge_method: model_stock
base_model: OpenPipe/mistral-ft-optimized-1227
dtype: bfloat16
Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "louisbrulenaudet/Maxine-7B-0401-stock"
messages = [{"role": "user", "content": "What is a large language model?"}]
tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
Citing & Authors
If you use this code in your research, please use the following BibTeX entry.
@misc{louisbrulenaudet2024,
author = {Louis Brulé Naudet},
title = {Maxine-7B-0401-stock, an xtraordinary 7B model},
year = {2024}
howpublished = {\url{https://huggingface.co/louisbrulenaudet/Maxine-7B-0401-stock}},
}
Feedback
If you have any feedback, please reach out at louisbrulenaudet@icloud.com.
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