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JSpergel/test_tiny_mixtral_only_router_2
test_tiny_mixtral_only_router_2 is a text generation model from JSpergel. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as apache-2.0.
testtinymixtralonlyrouter2 is a Mixture of Experts (MoE) made with the following models using LazyMergekit: openaccess-ai-collective/tiny-mistral openaccess-ai-collective/tiny-mistral
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From the Hugging Face model README
test_tiny_mixtral_only_router_2 is a Mixture of Experts (MoE) made with the following models using LazyMergekit:
base_model: openaccess-ai-collective/tiny-mistral
gate_mode: hidden
dtype: bfloat16
experts:
- source_model: openaccess-ai-collective/tiny-mistral
positive_prompts:
- "math"
# You can add negative_prompts if needed
- source_model: openaccess-ai-collective/tiny-mistral
positive_prompts:
- "science"
- source_model: openaccess-ai-collective/tiny-mistral
positive_prompts:
- "writing"
# You can add negative_prompts if needed
- source_model: openaccess-ai-collective/tiny-mistral
positive_prompts:
- "general"
!pip install -qU transformers bitsandbytes accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "JSpergel/test_tiny_mixtral_only_router_2"
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"])