microchar_moe
microchar_moe is a Mixture of Experts (MoE) made with the following models using LazyMergekit:
𧩠Configuration
base_model: Corianas/Microllama_Char_88k_step
gate_mode: random # one of "hidden", "cheap_embed", or "random"
dtype: bfloat16 # output dtype (float32, float16, or bfloat16)
## (optional)
# experts_per_token: 2
experts:
- source_model: Corianas/Microllama_Char_88k_step
positive_prompts:
- ""
## (optional)
# negative_prompts:
# - "This is a prompt expert_model_1 should not be used for"
- source_model: Corianas/Microllama_Char_88k_step
positive_prompts:
- ""
π» Usage
!pip install -qU transformers bitsandbytes accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Corianas/microchar_moe"
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"])
- Downloads last month
- 8
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for Corianas/microchar_moe
Base model
Corianas/Microllama_Char_88k_step