Row 2122

Row ID: 2122 | Dataset Entry | Axioma AXP Content Repository

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Hello!

I am new with using TF and just set up everything. I use one of the universal-sentence-encoder and have a bunch of different texts (\~2000) as input. The model then creates the specific embeddings.Now my plan is to calculate the three metrics of the model and visualize it then for this specific amount of input data.

my_model = hub.load("path-to-universal-sentence-encoder") my_texts = [...] my_embeddings = [my_model(text) for text in my_texts]

As I have the embeddings for each of my texts, what would be the next proper steps for determining and visualizing these metrics?

Thank you for any specific suggestions and for sharing your experience!

FieldValue
text Hello! I am new with using TF and just set up everything. I use one of the universal-sentence-encoder and have a bunch of different texts (\~2000) as input. The model then creates the specific embeddings.Now my plan is to calculate the three metrics of the model and visualize it then for this specific amount of input data. my_model = hub.load("path-to-universal-sentence-encoder") my_texts = [...] my_embeddings = [my_model(text) for text in my_texts] As I have the embeddings for ea…
label r/tensorflow
dataType post
communityName r/tensorflow
datetime 2023-06-27
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url_encoded Z0FBQUFBQm5Lak9FeFMzTGpRWU5WMEx0dEJjMlRaaVZDZmVkeTJQNUNHYnNIVzRKMkc4QmN3aVZJS2NaeFNHN0VVUHE2bGlFWXFlMlNDSlNxb3NPZVVLbmRBXzVnbGJSSl9nb25Vd3Myb1JrWFRCMlRWM2ZOcnVsTlZsNkdybk44cUJXRUJoTmVJWkkyMWxMdklsVVppSlpxQV9icUtrS1hHODhINjc5bjIwb2JFOFNtTF9XRFkxVXAtcmlmNGpTdTlWWUtzTEFXUzNlQzJKOXBfdWl4dVdjY2RmZVpHUFZZZz09

Raw Record

{
  "text": "Hello!\n\nI am new with using TF and just set up everything. I use one of the universal-sentence-encoder and have a bunch of different texts (\\~2000) as input. The model then creates the specific embeddings.Now my plan is to calculate the three metrics of the model and visualize it then for this specific amount of input data.\n\n    my_model = hub.load(\"path-to-universal-sentence-encoder\")\n    my_texts = [...]\n    my_embeddings = [my_model(text) for text in my_texts]\n\nAs I have the embeddings for each of my texts, what would be the next proper steps for determining and visualizing these metrics?\n\nThank you for any specific suggestions and for sharing your experience!",
  "label": "r/tensorflow",
  "dataType": "post",
  "communityName": "r/tensorflow",
  "datetime": "2023-06-27",
  "username_encoded": "Z0FBQUFBQm5LakwwUkJOWnpqN2pDdjJxSXVUTmMyTHFyRGtfSUtwWGRhRXdGbng2cEw4NjgzVXo0NXF5c0RXVzI0V2tSUVdLMVdHcU1zVm9LbnFzUE5INVFzdHJSMVVWWWc9PQ==",
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}
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