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1base_model: Corianas/Tiny_Test
2gate_mode: random # one of "hidden", "cheap_embed", or "random"
3dtype: bfloat16 # output dtype (float32, float16, or bfloat16)
4## (optional)
5# experts_per_token: 2
6experts:
7 - source_model: Corianas/Tiny_Test
8 positive_prompts:
9 - ""
10 ## (optional)
11 # negative_prompts:
12 # - "This is a prompt expert_model_1 should not be used for"
13 - source_model: Corianas/TinyTask-minipaca
14 positive_prompts:
15 - ""1!pip install -qU transformers bitsandbytes accelerate
2
3from transformers import AutoTokenizer
4import transformers
5import torch
6
7model = "Corianas/Tiny-moe-rand"
8
9tokenizer = AutoTokenizer.from_pretrained(model)
10pipeline = transformers.pipeline(
11 "text-generation",
12 model=model,
13 model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
14)
15
16messages = [{"role": "user", "content": "↨explain what a ↨mixture of ↨experts is in less than 100 words."}]
17prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
18outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
19print(outputs[0]["generated_text"])