Add T5-small LoRA-merged agentic github tagger

README.md

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+---
+language:
+  - en
+license: apache-2.0
+library_name: transformers
+base_model: google-t5/t5-small
+tags:
+  - peft
+  - t5
+  - agents
+  - rag
+  - llmops
+  - text2text-generation
+  - lora
+datasets:
+  - hharsha/agentic-github-meta
+pipeline_tag: text2text-generation
+widget:
+  - text: multi-agent platform with RAG, MCP, and observability
+  - text: looking for RAG hybrid search recall@k and reranking
+  - text: FastAPI Next.js agent backend with Docker Compose
+---
+
+# agentic-github-tagger
+
+Lightweight **text2text tag generator** for agentic AI / RAG / LLMOps GitHub-style
+descriptions. Fine-tuned from [`google-t5/t5-small`](https://huggingface.co/google-t5/t5-small)
+with **PEFT LoRA** on [`hharsha/agentic-github-meta`](https://huggingface.co/datasets/hharsha/agentic-github-meta),
+then **merged** into full small weights so `transformers` pipelines work out of the box on CPU.
+
+> This is a **~60M-param T5-small** tagger — **not** a 7B chat demo. Free Hub + CPU friendly.
+
+## LoRA config (training)
+
+| | |
+|---|---|
+| Base | `google-t5/t5-small` |
+| Method | PEFT LoRA then merge |
+| r | 16 |
+| alpha | 32 |
+| dropout | 0.05 |
+| target_modules | `q`, `v` |
+| Epochs | 2 (CPU) |
+| Batch size | 8 |
+| Dataset | [`hharsha/agentic-github-meta`](https://huggingface.co/datasets/hharsha/agentic-github-meta) |
+
+## Usage
+
+```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:
+
+```
+observable, multi-agent, rAG, mCP, observability, et-
+```
+
+## Links
+
+- Dataset: [`hharsha/agentic-github-meta`](https://huggingface.co/datasets/hharsha/agentic-github-meta)
+- Showcase: [`hharsha/agentic-systems-showcase`](https://huggingface.co/datasets/hharsha/agentic-systems-showcase)
+- Studio: [https://agentic-systems-studio.com](https://agentic-systems-studio.com)
+- GitHub: [https://github.com/hharsha98](https://github.com/hharsha98)
+
+## Intended use
+
+Auto-suggest comma-separated tags for agentic / RAG / LLMOps project listings and search demos.
+
+## Limitations
+
+Small model; tags can be generic or incomplete. Not for safety-critical labeling.

config.json

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+{
+  "architectures": [
+    "T5ForConditionalGeneration"
+  ],
+  "classifier_dropout": 0.0,
+  "d_ff": 2048,
+  "d_kv": 64,
+  "d_model": 512,
+  "decoder_start_token_id": 0,
+  "dense_act_fn": "relu",
+  "dropout_rate": 0.1,
+  "dtype": "float32",
+  "eos_token_id": 1,
+  "feed_forward_proj": "relu",
+  "initializer_factor": 1.0,
+  "is_decoder": false,
+  "is_encoder_decoder": true,
+  "is_gated_act": false,
+  "layer_norm_epsilon": 1e-06,
+  "model_type": "t5",
+  "n_positions": 512,
+  "num_decoder_layers": 6,
+  "num_heads": 8,
+  "num_layers": 6,
+  "output_past": true,
+  "pad_token_id": 0,
+  "relative_attention_max_distance": 128,
+  "relative_attention_num_buckets": 32,
+  "scale_decoder_outputs": true,
+  "task_specific_params": {
+    "summarization": {
+      "early_stopping": true,
+      "length_penalty": 2.0,
+      "max_length": 200,
+      "min_length": 30,
+      "no_repeat_ngram_size": 3,
+      "num_beams": 4,
+      "prefix": "summarize: "
+    },
+    "translation_en_to_de": {
+      "early_stopping": true,
+      "max_length": 300,
+      "num_beams": 4,
+      "prefix": "translate English to German: "
+    },
+    "translation_en_to_fr": {
+      "early_stopping": true,
+      "max_length": 300,
+      "num_beams": 4,
+      "prefix": "translate English to French: "
+    },
+    "translation_en_to_ro": {
+      "early_stopping": true,
+      "max_length": 300,
+      "num_beams": 4,
+      "prefix": "translate English to Romanian: "
+    }
+  },
+  "tie_word_embeddings": true,
+  "transformers_version": "5.17.0",
+  "use_cache": false,
+  "vocab_size": 32128
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "decoder_start_token_id": 0,
+  "eos_token_id": [
+    1
+  ],
+  "pad_token_id": 0,
+  "transformers_version": "5.17.0"
+}

model.safetensors

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+size 242041896

tokenizer_config.json

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+{
+  "backend": "tokenizers",
+  "clean_up_tokenization_spaces": true,
+  "eos_token": "</s>",
+  "extra_ids": 100,
+  "extra_special_tokens": [
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+  "is_local": false,
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+  "tokenizer_class": "T5Tokenizer",
+  "unk_token": "<unk>"
+}

training_metadata.json

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+{
+  "base_model": "google-t5/t5-small",
+  "lora": {
+    "r": 16,
+    "alpha": 32,
+    "dropout": 0.05,
+    "target_modules": [
+      "q",
+      "v"
+    ]
+  },
+  "epochs": 2,
+  "batch_size": 8,
+  "train_rows": 600,
+  "sample_input": "multi-agent platform with RAG, MCP, and observability",
+  "sample_output": "observable, multi-agent, rAG, mCP, observability, et-",
+  "merged": true
+}