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smolified-semester-saver/README.md
ModelHub XC 486866a62c 初始化项目,由ModelHub XC社区提供模型
Model: anu-28/smolified-semester-saver
Source: Original Platform
2026-05-20 00:16:52 +08:00

2.3 KiB

license, language, tags, pipeline_tag, inference
license language tags pipeline_tag inference
apache-2.0
en
text-generation-inference
transformers
smolify
dslm
text-generation
parameters
temperature top_p top_k
1 0.95 64

🤏 smolified-semester-saver

Intelligence, Distilled.

This is a Domain Specific Language Model (DSLM) generated by the Smolify Foundry.

It has been synthetically distilled from SOTA reasoning engines into a high-efficiency architecture, optimized for deployment on edge hardware (CPU/NPU) or low-VRAM environments.

📦 Asset Details

  • Origin: Smolify Foundry (Job ID: 5f9c0f0b)
  • Architecture: gemma-3-270m
  • Training Method: Proprietary Neural Distillation
  • Optimization: 4-bit Quantized / FP16 Mixed
  • Dataset: Link to Dataset

🚀 Usage (Inference)

This model is compatible with standard inference backends like vLLM, and Hugging Face Transformers.

# Example: Running your Sovereign Model
from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "anu-28/smolified-semester-saver"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto")

messages = [
    {"role": "system", "content": '''You are a MAKAUT engineering professor expert in Electromagnetism.'''},
    {"role": "user", "content": '''Faraday's Law of Induction describes the relationship between a time-varying magnetic field and the electric field it induces. It states that the magnitude of the induced EMF is directly proportional to the rate of change of the magnetic flux through the circuit, as quantified by E = -dΦ/dt.'''}
]
text = tokenizer.apply_chat_template(
    messages,
    tokenize = False,
    add_generation_prompt = True,
)
if "gemma-3-270m" == "gemma-3-270m":
    text = text.removeprefix('<bos>')

from transformers import TextStreamer
_ = model.generate(
    **tokenizer(text, return_tensors = "pt").to(model.device),
    max_new_tokens = 1000,
    temperature = 1.0, top_p = 0.95, top_k = 64,
    streamer = TextStreamer(tokenizer, skip_prompt = True),
)

⚖️ License & Ownership

This model weights are a sovereign asset owned by anu-28. Generated via Smolify.ai.