mahiatlinux / SupaSigmer-test

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text-generation

Introduction of SupaSigmer-test

Model Details of SupaSigmer-test

SupaSigmer-test

SupaSigmer-test is a Mixture of Experts (MoE) made with the following models using LazyMergekit :

🧩 Configuration
base_model: mahiatlinux/Sigmer-150M
experts:
  - source_model: mahiatlinux/Sigmer-150M
    positive_prompts:
    - "chat"
    - "assistant"
    - "tell me"
    - "explain"
    - "I want"
  - source_model: mahiatlinux/Sigmer-150M
    positive_prompts:
    - "code"
    - "python"
    - "javascript"
    - "programming"
    - "algorithm"
  - source_model: mahiatlinux/Sigmer-150M
    positive_prompts:
    - "storywriting"
    - "write"
    - "scene"
    - "story"
    - "character"
  - source_model: mahiatlinux/Sigmer-150M
    positive_prompts:
    - "reason"
    - "math"
    - "mathematics"
    - "solve"
    - "count"
  - source_model: mahiatlinux/Sigmer-150M
    positive_prompts:
    - "science"
    - "biology"
    - "chemistry"
    - "physics"
    - "experiment"
  - source_model: mahiatlinux/Sigmer-150M
    positive_prompts:
    - "history"
    - "past"
    - "events"
    - "timeline"
    - "chronology"
  - source_model: mahiatlinux/Sigmer-150M
    positive_prompts:
    - "art"
    - "painting"
    - "sculpture"
    - "drawing"
    - "creativity"
  - source_model: mahiatlinux/Sigmer-150M
    positive_prompts:
    - "music"
    - "song"
    - "instrument"
    - "composition"
    - "melody"
💻 Usage
!pip install -qU transformers bitsandbytes accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "mahiatlinux/SupaSigmer-test"

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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More SupaSigmer-test license Visit here:

https://choosealicense.com/licenses/apache-2.0

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mahiatlinux SupaSigmer-test online free

SupaSigmer-test huggingface.co is an online trial and call api platform, which integrates SupaSigmer-test's modeling effects, including api services, and provides a free online trial of SupaSigmer-test, you can try SupaSigmer-test online for free by clicking the link below.

mahiatlinux SupaSigmer-test online free url in huggingface.co:

https://huggingface.co/mahiatlinux/SupaSigmer-test

SupaSigmer-test install

SupaSigmer-test is an open source model from GitHub that offers a free installation service, and any user can find SupaSigmer-test on GitHub to install. At the same time, huggingface.co provides the effect of SupaSigmer-test install, users can directly use SupaSigmer-test installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

SupaSigmer-test install url in huggingface.co:

https://huggingface.co/mahiatlinux/SupaSigmer-test

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mahiatlinux
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