commit files to HF hub

README.md

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+---
+language: "en"
+thumbnail: "Keywords to Sentences"
+tags:
+- keytotext
+- k2t
+- Keywords to Sentences
+license: "MIT"
+datasets:
+- WebNLG
+- Dart 
+metrics:
+- NLG
+
+model-index:
+- name: k2t-test3
+---
+        
+#keytotext
+
+[![pypi Version](https://img.shields.io/pypi/v/keytotext.svg?logo=pypi&logoColor=white)](https://pypi.org/project/keytotext/)
+[![Downloads](https://static.pepy.tech/personalized-badge/keytotext?period=total&units=none&left_color=grey&right_color=orange&left_text=Pip%20Downloads)](https://pepy.tech/project/keytotext)
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/gagan3012/keytotext/blob/master/notebooks/K2T.ipynb)
+[![Streamlit App](https://static.streamlit.io/badges/streamlit_badge_black_white.svg)](https://share.streamlit.io/gagan3012/keytotext/UI/app.py)
+[![API Call](https://img.shields.io/badge/-FastAPI-red?logo=fastapi&labelColor=white)](https://github.com/gagan3012/keytotext#api)
+[![Docker Call](https://img.shields.io/badge/-Docker%20Image-blue?logo=docker&labelColor=white)](https://hub.docker.com/r/gagan30/keytotext)
+[![HuggingFace](https://img.shields.io/badge/%F0%9F%A4%97-Models%20on%20Hub-yellow)](https://huggingface.co/models?filter=keytotext)
+[![Documentation Status](https://readthedocs.org/projects/keytotext/badge/?version=latest)](https://keytotext.readthedocs.io/en/latest/?badge=latest)
+[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
+
+
+
+![keytotext](https://socialify.git.ci/gagan3012/keytotext/image?description=1&forks=1&language=1&owner=1&stargazers=1&theme=Light)
+
+
+Idea is to build a model which will take keywords as inputs and generate sentences as outputs.
+
+Potential use case can include: 
+- Marketing 
+- Search Engine Optimization
+- Topic generation etc.
+- Fine tuning of topic modeling models

config.json

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+{
+  "_name_or_path": "t5-small",
+  "architectures": [
+    "T5ForConditionalGeneration"
+  ],
+  "d_ff": 2048,
+  "d_kv": 64,
+  "d_model": 512,
+  "decoder_start_token_id": 0,
+  "dropout_rate": 0.1,
+  "eos_token_id": 1,
+  "feed_forward_proj": "relu",
+  "gradient_checkpointing": false,
+  "initializer_factor": 1.0,
+  "is_encoder_decoder": true,
+  "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_num_buckets": 32,
+  "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: "
+    }
+  },
+  "transformers_version": "4.8.2",
+  "use_cache": true,
+  "vocab_size": 32128
+}

pytorch_model.bin

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special_tokens_map.json

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spiece.model

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tokenizer_config.json

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