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Update app.py
Browse files
app.py
CHANGED
@@ -43,12 +43,12 @@ def Page():
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solara.Markdown(f'{spans1}')
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outputs = model.generate(tokens, max_new_tokens=2, output_scores=True, return_dict_in_generate=True, pad_token_id=tokenizer.eos_token_id)
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scores = F.softmax(outputs.scores[0], dim=-1)
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top_10 = torch.topk(scores,
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df = pd.DataFrame()
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df["probs"] = top_10.values[0]
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df["probs"] = [f"{value:.2%}" for value in df["probs"].values]
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df["next token ID"] = [top_10.indices[0][i].numpy() for i in range(
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df["predicted next token"] = [tokenizer.decode(top_10.indices[0][i]) for i in range(
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solara.Markdown("###Prediction")
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solara.DataFrame(df, items_per_page=10, cell_actions=cell_actions)
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Page()
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solara.Markdown(f'{spans1}')
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outputs = model.generate(tokens, max_new_tokens=2, output_scores=True, return_dict_in_generate=True, pad_token_id=tokenizer.eos_token_id)
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scores = F.softmax(outputs.scores[0], dim=-1)
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top_10 = torch.topk(scores, 1000)
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df = pd.DataFrame()
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df["probs"] = top_10.values[0]
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df["probs"] = [f"{value:.2%}" for value in df["probs"].values]
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df["next token ID"] = [top_10.indices[0][i].numpy() for i in range(1000)]
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df["predicted next token"] = [tokenizer.decode(top_10.indices[0][i]) for i in range(1000)]
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solara.Markdown("###Prediction")
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solara.DataFrame(df, items_per_page=10, cell_actions=cell_actions)
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Page()
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