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https://github.com/oobabooga/text-generation-webui.git
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Use a list of eos_tokens instead of just a number
This might be the cause of LLaMA ramblings that some people have experienced.
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@ -119,7 +119,9 @@ def generate_reply(question, max_new_tokens, do_sample, temperature, top_p, typi
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original_input_ids = input_ids
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output = input_ids[0]
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cuda = "" if (shared.args.cpu or shared.args.deepspeed or shared.args.flexgen) else ".cuda()"
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n = shared.tokenizer.eos_token_id if eos_token is None else int(encode(eos_token)[0][-1])
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eos_token_ids = [shared.tokenizer.eos_token_id]
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if eos_token is not None:
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eos_token_ids.append(int(encode(eos_token)[0][-1]))
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stopping_criteria_list = transformers.StoppingCriteriaList()
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if stopping_string is not None:
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# Copied from https://github.com/PygmalionAI/gradio-ui/blob/master/src/model.py
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@ -129,7 +131,7 @@ def generate_reply(question, max_new_tokens, do_sample, temperature, top_p, typi
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if not shared.args.flexgen:
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generate_params = [
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f"max_new_tokens=max_new_tokens",
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f"eos_token_id={n}",
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f"eos_token_id={eos_token_ids}",
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f"stopping_criteria=stopping_criteria_list",
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f"do_sample={do_sample}",
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f"temperature={temperature}",
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@ -149,7 +151,7 @@ def generate_reply(question, max_new_tokens, do_sample, temperature, top_p, typi
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f"max_new_tokens={max_new_tokens if shared.args.no_stream else 8}",
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f"do_sample={do_sample}",
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f"temperature={temperature}",
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f"stop={n}",
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f"stop={eos_token_ids[-1]}",
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]
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if shared.args.deepspeed:
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generate_params.append("synced_gpus=True")
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@ -198,7 +200,7 @@ def generate_reply(question, max_new_tokens, do_sample, temperature, top_p, typi
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if not (shared.args.chat or shared.args.cai_chat):
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reply = original_question + apply_extensions(reply[len(question):], "output")
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if output[-1] == n:
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if output[-1] in eos_token_ids:
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break
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yield formatted_outputs(reply, shared.model_name)
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@ -219,7 +221,7 @@ def generate_reply(question, max_new_tokens, do_sample, temperature, top_p, typi
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if not (shared.args.chat or shared.args.cai_chat):
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reply = original_question + apply_extensions(reply[len(question):], "output")
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if np.count_nonzero(input_ids[0] == n) < np.count_nonzero(output == n):
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if np.count_nonzero(np.isin(input_ids[0], eos_token_ids)) < np.count_nonzero(np.isin(output, eos_token_ids)):
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break
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yield formatted_outputs(reply, shared.model_name)
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