Proximus-2x7B-v1
Proximus-2x7B-v1 is a Mixure of Experts (MoE) made with the following models using LazyMergekit:
🧩 Configuration
base_model: mlabonne/NeuralHermes-2.5-Mistral-7B
experts:
- source_model: beowolx/MistralHermes-CodePro-7B-v1
positive_prompts:
- "code"
- "python"
- "javascript"
- "programming"
- "algorithm"
- source_model: preemware/Prox-MistralHermes-7B
positive_prompts:
- "cybersecurity"
- "information security"
- "network security"
- "hacking"
- "encryption"
💻 Usage
!pip install -qU transformers bitsandbytes accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "preemware/Proximus-2x7B-v1"
tokenizer = AutoTokenizer.from_pretrained(model)
pipeline = transformers.pipeline(
"text-generation",
model=model,
model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
)
messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}]
prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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"])