model update

README.md

@@ -0,0 +1,28 @@
+
+---
+widget:
+- text: "generate analogy: mammal is to whale"
+  example_title: "Analogy Example 1 (semantic relation)"
+- text: "generate analogy: wedding is to marriage"
+  example_title: "Analogy Example 1 (semantic relation, metaphor)"
+- text: "generate analogy: London is to U.K."
+  example_title: "Analogy Example 2 (entity)"
+- text: "generate analogy: actual is to actually"
+  example_title: "Analogy Example 3 (morphological)"
+---
+# relbert/flan-t5-large-analogy-t-rex
+
+This is [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) fine-tuned on [relbert/t_rex_relational_similarity](https://huggingface.co/datasets/relbert/t_rex_relational_similarity) 
+for analogy generation, which is to generate a word pair (eg. `bird is to crow`) given a query (eg. `mammal is to whale`) 
+so that the query and the generated word pair form an analogy statement.  
+
+### Usage
+
+```python
+from transformers import pipeline
+
+pipe = pipeline('text2text-generation', model="relbert/flan-t5-large-analogy-t-rex")
+output = pipe("generate analogy: mammal is to whale")
+print(output)
+>>> [{'generated_text': 'bird is to crow'}]
+```

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "analogy_models/flan-t5-large-analogy-t-rex-epoch3/model",
+  "_name_or_path": "google/flan-t5-large",
   "architectures": [
     "T5ForConditionalGeneration"
   ],

pytorch_model.bin

@@ -1,3 +1,3 @@
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tokenizer_config.json

@@ -104,7 +104,7 @@
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   "extra_ids": 100,
   "model_max_length": 512,
-  "name_or_path": "analogy_models/flan-t5-large-analogy-t-rex-epoch3/model",
+  "name_or_path": "google/flan-t5-large",
   "pad_token": "<pad>",
   "sp_model_kwargs": {},
   "special_tokens_map_file": "/home/younes_huggingface_co/.cache/huggingface/hub/models--google--t5-v1_1-large/snapshots/314bc112b191ec17b625ba81438dc73d6c23659d/special_tokens_map.json",

training_args.bin

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validation_accuracy.json

@@ -0,0 +1 @@
+{"accuracy": 0.21428571428571427, "dataset": "relbert/t_rex_relational_similarity", "split": "validation"}