Update low level api example
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5f2e822b59
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5e011145c5
1 changed files with 5 additions and 5 deletions
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@ -35,7 +35,7 @@ remaining_tokens = n_predict
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embd = []
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embd = []
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last_n_size = 64
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last_n_size = 64
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last_n_tokens = [0] * last_n_size
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last_n_tokens_data = [0] * last_n_size
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n_batch = 24
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n_batch = 24
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while remaining_tokens > 0:
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while remaining_tokens > 0:
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@ -49,21 +49,21 @@ while remaining_tokens > 0:
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if len(embd_inp) <= input_consumed:
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if len(embd_inp) <= input_consumed:
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id = llama_cpp.llama_sample_top_p_top_k(
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id = llama_cpp.llama_sample_top_p_top_k(
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ctx,
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ctx,
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(llama_cpp.c_int * len(last_n_tokens))(*last_n_tokens),
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(llama_cpp.c_int * len(last_n_tokens_data))(*last_n_tokens_data),
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len(last_n_tokens),
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len(last_n_tokens_data),
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40,
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40,
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0.8,
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0.8,
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0.2,
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0.2,
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1.0 / 0.85,
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1.0 / 0.85,
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)
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)
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last_n_tokens = last_n_tokens[1:] + [id]
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last_n_tokens_data = last_n_tokens_data[1:] + [id]
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embd.append(id)
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embd.append(id)
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input_noecho = False
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input_noecho = False
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remaining_tokens -= 1
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remaining_tokens -= 1
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else:
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else:
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while len(embd_inp) > input_consumed:
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while len(embd_inp) > input_consumed:
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embd.append(embd_inp[input_consumed])
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embd.append(embd_inp[input_consumed])
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last_n_tokens = last_n_tokens[1:] + [embd_inp[input_consumed]]
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last_n_tokens_data = last_n_tokens_data[1:] + [embd_inp[input_consumed]]
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input_consumed += 1
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input_consumed += 1
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if len(embd) >= n_batch:
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if len(embd) >= n_batch:
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break
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break
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