weqweasdas
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RM-Gemma-2B

Text Classification

text-generation-inference

Inference Endpoints

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weqweasdas commited on Feb 25

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3042537

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1 Parent(s): 6ac4b2e

Update README.md

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@@ -74,7 +74,7 @@ We train the model for one epoch with a learning rate of 1e-5, batch size 256, c
    {"role": "user", "content": "I'd like to show off how chat templating works!"},
   ]
-  test_texts = tokenizer.apply_chat_template(chat, tokenize=False, add_generation_prompt=False).replace(tokenizer.bos_token, "")
   pipe_outputs = rm_pipe(test_texts, **pipe_kwargs)
   rewards = [output[0]["score"] for output in pipe_outputs]
 ```

    {"role": "user", "content": "I'd like to show off how chat templating works!"},
   ]
+  test_texts = [tokenizer.apply_chat_template(chat, tokenize=False, add_generation_prompt=False).replace(tokenizer.bos_token, "")]
   pipe_outputs = rm_pipe(test_texts, **pipe_kwargs)
   rewards = [output[0]["score"] for output in pipe_outputs]
 ```