commit files to HF hub

README.md

@@ -1,42 +1,19 @@
 ---
-language: en
-thumbnail: Keywords to Sentences
+language: "en"
+thumbnail: "Keywords to Sentences"
 tags:
 - keytotext
 - k2t
 - Keywords to Sentences
-license: mit
-datasets:
-- WebNLG
-- Dart
-metrics:
-- NLG
+
+model-index:
+- name: t5-small
 ---
-# keytotext
-![keytotext (1)](https://user-images.githubusercontent.com/49101362/116334480-f5e57a00-a7dd-11eb-987c-186477f94b6e.png)
-Idea is to build a model which will take keywords as inputs and generate sentences as outputs. 
-### Keytotext is powered by Huggingface 🤗
-[![pypi Version](https://img.shields.io/pypi/v/keytotext.svg?style=flat-square&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/Examples/K2T.ipynb)
-[![Streamlit App](https://static.streamlit.io/badges/streamlit_badge_black_white.svg)](https://share.streamlit.io/gagan3012/keytotext/UI/app.py)
-## Model:
-Keytotext is based on the Amazing T5 Model: 
-- `k2t`: [Model](https://huggingface.co/gagan3012/k2t)
-- `k2t-tiny`: [Model](https://huggingface.co/gagan3012/k2t-tiny)
-- `k2t-base`: [Model](https://huggingface.co/gagan3012/k2t-base)
-Training Notebooks can be found in the [`Training Notebooks`](https://github.com/gagan3012/keytotext/tree/master/Training%20Notebooks) Folder
-## Usage:
-Example usage: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/gagan3012/keytotext/blob/master/Examples/K2T.ipynb)
-Example Notebooks can be found in the [`Notebooks`](https://github.com/gagan3012/keytotext/tree/master/Examples) Folder
-```
-pip install keytotext
-```
-![carbon (3)](https://user-images.githubusercontent.com/49101362/116220679-90e64180-a755-11eb-9246-82d93d924a6c.png)
-## UI:
-UI: [![Streamlit App](https://static.streamlit.io/badges/streamlit_badge_black_white.svg)](https://share.streamlit.io/gagan3012/keytotext/UI/app.py)
-```
-pip install streamlit-tags
-```
-This uses a custom streamlit component built by me: [GitHub](https://github.com/gagan3012/streamlit-tags)
-![image](https://user-images.githubusercontent.com/49101362/116162205-fc042980-a6fd-11eb-892e-8f6902f193f4.png)
+
+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

@@ -0,0 +1,57 @@
+{
+  "_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",
+  "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: "
+    }
+  },
+  "torch_dtype": "float32",
+  "transformers_version": "4.15.0",
+  "use_cache": true,
+  "vocab_size": 32128
+}

pytorch_model.bin

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special_tokens_map.json

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tokenizer_config.json

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