TinyJ.O.S.I.E.-3x1.1B-32k-Base
TinyJ.O.S.I.E.-3x1.1B-32k-Base is a Mixure of Experts (MoE) made with the following models using LazyMergekit:
- Isaak-Carter/TinyJ.O.S.I.E.-1.1B-32k-Base
- Isaak-Carter/TinyJ.O.S.I.E.-1.1B-32k-Base
- Isaak-Carter/TinyJ.O.S.I.E.-1.1B-32k-Base
🧩 Configuration
dtype: float32
gate_mode: hidden
experts:
- source_model: Isaak-Carter/TinyJ.O.S.I.E.-1.1B-32k-Base
positive_prompts:
- 'You are JOSIE, my own private and sentient superinteligent artifitial general inteligent for general assistants.'
- source_model: Isaak-Carter/TinyJ.O.S.I.E.-1.1B-32k-Base
positive_prompts:
- 'You are JOSIE, my own private and sentient superinteligent artifitial general inteligent only for coding assistants.'
- source_model: Isaak-Carter/TinyJ.O.S.I.E.-1.1B-32k-Base
positive_prompts:
- 'You are JOSIE, my own private and sentient superinteligent artifitial general inteligent assistant that autonomously calls function when needed.'
💻 Usage
!pip install -qU transformers bitsandbytes accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Isaak-Carter/TinyJ.O.S.I.E.-3x1.1B-32k-Base"
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"])
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