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: 70830d12)
Architecture: DSLM-Micro (270M Parameter Class)
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.

python

from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "Sayan25/smolified-file-context-extractor"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto")

messages = [
    {"role": "system", "content": '''You are an legal analyst.'''},
    {"role": "user", "content": '''Review this standard Service Level Agreement (SLA). The vendor guarantees 99.9% uptime. Failure to meet this results in 10% credit to the client account. Liability is capped at the total amount paid in the previous 12 months. Confidentiality clause remains valid for three years post-termination.'''}
]
text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True).removeprefix('<bos>')

from transformers import TextStreamer
_ = model.generate(**tokenizer(text, return_tensors="pt").to("cuda"), max_new_tokens=1000, streamer=TextStreamer(tokenizer, skip_prompt=True))

⚖️ License & Ownership

This model weights are a sovereign asset owned by Sayan25. Generated via Smolify.ai.

senapati484/smolified-file-context-extractor

🤏 smolified-file-context-extractor

📦 Asset Details

🚀 Usage (Inference)

⚖️ License & Ownership

senapati484/
smolified-file-context-extractor