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hharsha/agentic-github-tagger

sourceHugging Faceapache-2.0updated 7d agoView on Hugging Face
1likes144downloads
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agentic-github-tagger

Lightweight text2text tag generator for agentic AI / RAG / LLMOps GitHub-style descriptions. Fine-tuned from `google-t5/t5-small` with PEFT LoRA (r=16, alpha=32, dropout=0.05, target_modules q,v) on `hharsha/agentic-github-meta`, then merged so full small weights load on free CPU.

~60M-param T5-small tagger — not a 7B chat demo. Free Hub + CPU friendly.

Usage

python
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer

model_id = "hharsha/agentic-github-tagger"
tok = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForSeq2SeqLM.from_pretrained(model_id)

text = "multi-agent platform with RAG, MCP, and observability"
ids = tok(text, return_tensors="pt")
out = model.generate(**ids, max_new_tokens=64, num_beams=4)
print(tok.decode(out[0], skip_special_tokens=True))

On older transformers that still register the task, this also works:

python
from transformers import pipeline
pipe = pipeline("text2text-generation", model="hharsha/agentic-github-tagger")
print(pipe("multi-agent platform with RAG, MCP, and observability")[0]["generated_text"])

Sample output from this training run:

multi-agent, multi-agent, observability, rag, mCP, observability

Training

Basegoogle-t5/t5-small
MethodPEFT LoRA then merge
r / alpha / dropout16 / 32 / 0.05
target_modulesq, v
Epochs3 (CPU)
Batch size8
Dataset`hharsha/agentic-github-meta` (687 rows; 600 used for train)

Links

Intended use / limits

Auto-suggest comma-separated tags for agentic / RAG / LLMOps project listings. Small model; tags can repeat or be incomplete. Not for safety-critical labeling.