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sugatobagchi/smolified-transcripts-checker
smolified-transcripts-checker is a text generation model from sugatobagchi. 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.
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From the Hugging Face model README
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.
3a495556)This model is compatible with standard inference backends like vLLM.
# Example: Running your Sovereign Model
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "sugatobagchi/smolified-transcripts-checker"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto")
messages = [
{'role': 'system', 'content': '''Client Style Guide: 1. Numbers 0-9 spelled out, 10+ digits. 2. Speaker labels in all caps followed by a colon. 3. US currency uses '$' prefix. 4. Dates in 'Month Day, Year' format. 5. 'uh' and 'um' removed. 6. Sentences with any potential error, ambiguity, or awkwardness are flagged with '[??]' at the end.'''},
{'role': 'user', 'content': '''Interviewer: We're talking about four key points here. Participant: Yes. Exactly four points to cover. Not three, not five.'''}
]
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,
temperature = 1, top_p = 0.95, top_k = 64,
streamer = TextStreamer(tokenizer, skip_prompt = True),
)
This model weights are a sovereign asset owned by sugatobagchi. Generated via Smolify.ai.