Mistral-CultriX-slerp
Research & Development for AutoSynthetix AI
🌐 Website https://autosynthetix.com/
📨 Discord https://discord.gg/pAKqENStQr
📦 GitHub https://github.com/jdwebprogrammer
📦 GitLab https://gitlab.com/jdwebprogrammer
🏆 Patreon https://patreon.com/jdwebprogrammer
📷 YouTube https://www.youtube.com/@jdwebprogrammer
📺 Twitch https://www.twitch.tv/jdwebprogrammer
🐦 Twitter(X) https://twitter.com/jdwebprogrammer
- License includes the license of the model derivatives:
- MergeKit LGPL-3.0 https://github.com/arcee-ai/mergekit?tab=LGPL-3.0-1-ov-file#readme
- Mistral Apache 2.0 https://huggingface.co/mistralai/Mistral-7B-v0.1
- CultriX Apache 2.0 https://huggingface.co/CultriX/NeuralTrix-7B-dpo
Mistral-CultriX-slerp is a merge of the following models using LazyMergekit:
🧩 Configuration
slices:
- sources:
- model: mistralai/Mistral-7B-v0.1
layer_range: [0, 32]
- model: CultriX/NeuralTrix-7B-dpo
layer_range: [0, 32]
merge_method: slerp
base_model: mistralai/Mistral-7B-v0.1
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
dtype: bfloat16
💻 Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "JDWebProgrammer/Mistral-CultriX-slerp"
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"])