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https://github.com/oobabooga/text-generation-webui.git
synced 2024-10-01 01:26:03 -04:00
Add skip_special_tokens checkbox for Dolly model (#1218)
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@ -42,9 +42,10 @@ async def run(context):
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'early_stopping': False,
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'seed': -1,
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'add_bos_token': True,
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'truncation_length': 2048,
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'custom_stopping_strings': [],
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'ban_eos_token': False
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'truncation_length': 2048,
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'ban_eos_token': False,
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'skip_special_tokens': True,
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}
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payload = json.dumps([context, params])
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session = random_hash()
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@ -39,6 +39,7 @@ params = {
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'custom_stopping_strings': [],
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'truncation_length': 2048,
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'ban_eos_token': False,
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'skip_special_tokens': True,
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}
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# Input prompt
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@ -61,6 +61,7 @@ class Handler(BaseHTTPRequestHandler):
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'custom_stopping_strings': body.get('custom_stopping_strings', []),
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'truncation_length': int(body.get('truncation_length', 2048)),
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'ban_eos_token': bool(body.get('ban_eos_token', False)),
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'skip_special_tokens': bool(body.get('skip_special_tokens', True)),
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}
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generator = generate_reply(
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@ -4,6 +4,8 @@
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groupsize: 'None'
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pre_layer: 0
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mode: 'cai-chat'
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skip_special_tokens: true
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custom_stopping_strings: ''
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llama-[0-9]*b-4bit$:
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wbits: 4
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model_type: 'llama'
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@ -33,3 +35,10 @@ llama-[0-9]*b-4bit$:
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instruction_template: 'Alpaca'
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wbits: 4
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groupsize: 128
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.*(galactica|oasst):
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skip_special_tokens: false
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.*dolly-v[0-9]-[0-9]*b:
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mode: 'instruct'
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instruction_template: 'Alpaca'
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skip_special_tokens: false
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custom_stopping_strings: '"### End"'
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@ -41,6 +41,7 @@ settings = {
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'stop_at_newline': False,
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'add_bos_token': True,
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'ban_eos_token': False,
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'skip_special_tokens': True,
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'truncation_length': 2048,
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'truncation_length_min': 0,
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'truncation_length_max': 4096,
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@ -57,14 +57,13 @@ def encode(prompt, add_special_tokens=True, add_bos_token=True, truncation_lengt
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return input_ids.cuda()
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def decode(output_ids):
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# Open Assistant relies on special tokens like <|endoftext|>
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if re.match('.*(oasst|galactica)-*', shared.model_name.lower()):
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return shared.tokenizer.decode(output_ids, skip_special_tokens=False)
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else:
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def decode(output_ids, skip_special_tokens=True):
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if skip_special_tokens:
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reply = shared.tokenizer.decode(output_ids, skip_special_tokens=True)
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reply = reply.replace(r'<|endoftext|>', '')
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return reply
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else:
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return shared.tokenizer.decode(output_ids, skip_special_tokens=False)
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def generate_softprompt_input_tensors(input_ids):
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@ -184,7 +183,7 @@ def generate_reply(question, state, eos_token=None, stopping_strings=[]):
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output = input_ids[0]
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if shared.args.verbose:
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print(f'\n\n{decode(input_ids[0])}\n--------------------\n')
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print(f'\n\n{decode(input_ids[0], state["skip_special_tokens"])}\n--------------------\n')
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cuda = not any((shared.args.cpu, shared.args.deepspeed, shared.args.flexgen))
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eos_token_ids = [shared.tokenizer.eos_token_id] if shared.tokenizer.eos_token_id is not None else []
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@ -231,11 +230,12 @@ def generate_reply(question, state, eos_token=None, stopping_strings=[]):
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output = shared.model.generate(**generate_params)[0]
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if cuda:
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output = output.cuda()
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if shared.soft_prompt:
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output = torch.cat((input_ids[0], output[filler_input_ids.shape[1]:]))
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new_tokens = len(output) - len(input_ids[0])
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reply = decode(output[-new_tokens:])
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reply = decode(output[-new_tokens:], state['skip_special_tokens'])
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if not shared.is_chat():
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reply = original_question + apply_extensions(reply, 'output')
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@ -256,18 +256,20 @@ def generate_reply(question, state, eos_token=None, stopping_strings=[]):
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if not shared.is_chat():
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yield formatted_outputs(original_question, shared.model_name)
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with generate_with_streaming(**generate_params) as generator:
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for output in generator:
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if shared.soft_prompt:
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output = torch.cat((input_ids[0], output[filler_input_ids.shape[1]:]))
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new_tokens = len(output) - len(input_ids[0])
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reply = decode(output[-new_tokens:])
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reply = decode(output[-new_tokens:], state['skip_special_tokens'])
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if not shared.is_chat():
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reply = original_question + apply_extensions(reply, 'output')
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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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# Stream the output naively for FlexGen since it doesn't support 'stopping_criteria'
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@ -276,18 +278,19 @@ def generate_reply(question, state, eos_token=None, stopping_strings=[]):
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clear_torch_cache()
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with torch.no_grad():
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output = shared.model.generate(**generate_params)[0]
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if shared.soft_prompt:
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output = torch.cat((input_ids[0], output[filler_input_ids.shape[1]:]))
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new_tokens = len(output) - len(original_input_ids[0])
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reply = decode(output[-new_tokens:])
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reply = decode(output[-new_tokens:], state['skip_special_tokens'])
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if not shared.is_chat():
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reply = original_question + apply_extensions(reply, 'output')
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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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yield formatted_outputs(reply, shared.model_name)
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input_ids = np.reshape(output, (1, output.shape[0]))
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if shared.soft_prompt:
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inputs_embeds, filler_input_ids = generate_softprompt_input_tensors(input_ids)
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@ -25,7 +25,7 @@ def list_model_elements():
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def list_interface_input_elements(chat=False):
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elements = ['max_new_tokens', 'seed', 'temperature', 'top_p', 'top_k', 'typical_p', 'repetition_penalty', 'encoder_repetition_penalty', 'no_repeat_ngram_size', 'min_length', 'do_sample', 'penalty_alpha', 'num_beams', 'length_penalty', 'early_stopping', 'add_bos_token', 'ban_eos_token', 'truncation_length', 'custom_stopping_strings']
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elements = ['max_new_tokens', 'seed', 'temperature', 'top_p', 'top_k', 'typical_p', 'repetition_penalty', 'encoder_repetition_penalty', 'no_repeat_ngram_size', 'min_length', 'do_sample', 'penalty_alpha', 'num_beams', 'length_penalty', 'early_stopping', 'add_bos_token', 'ban_eos_token', 'truncation_length', 'custom_stopping_strings', 'skip_special_tokens']
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if chat:
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elements += ['name1', 'name2', 'greeting', 'context', 'end_of_turn', 'chat_prompt_size', 'chat_generation_attempts', 'stop_at_newline', 'mode', 'instruction_template']
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elements += list_model_elements()
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@ -424,7 +424,9 @@ def create_settings_menus(default_preset):
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with gr.Group():
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with gr.Row():
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shared.gradio['add_bos_token'] = gr.Checkbox(value=shared.settings['add_bos_token'], label='Add the bos_token to the beginning of prompts', info='Disabling this can make the replies more creative.')
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shared.gradio['ban_eos_token'] = gr.Checkbox(value=shared.settings['ban_eos_token'], label='Ban the eos_token', info='This forces the model to never end the generation prematurely.')
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shared.gradio['ban_eos_token'] = gr.Checkbox(value=shared.settings['ban_eos_token'], label='Ban the eos_token', info='Forces the model to never end the generation prematurely.')
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shared.gradio['skip_special_tokens'] = gr.Checkbox(value=shared.settings['skip_special_tokens'], label='Skip special tokens', info='Some specific models need this unset.')
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shared.gradio['truncation_length'] = gr.Slider(value=shared.settings['truncation_length'], minimum=shared.settings['truncation_length_min'], maximum=shared.settings['truncation_length_max'], step=1, label='Truncate the prompt up to this length', info='The leftmost tokens are removed if the prompt exceeds this length. Most models require this to be at most 2048.')
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shared.gradio['custom_stopping_strings'] = gr.Textbox(lines=1, value=shared.settings["custom_stopping_strings"] or None, label='Custom stopping strings', info='In addition to the defaults. Written between "" and separated by commas. For instance: "\\nYour Assistant:", "\\nThe assistant:"')
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@ -766,7 +768,7 @@ def create_interface():
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chat.redraw_html, reload_inputs, shared.gradio['display'])
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shared.gradio['instruction_template'].change(
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lambda character, name1, name2, mode: chat.load_character(character, name1, name2, mode), [shared.gradio[k] for k in ['instruction_template', 'name1', 'name2', 'mode']], [shared.gradio[k] for k in ['name1', 'name2', 'character_picture', 'greeting', 'context', 'end_of_turn', 'display']]).then(
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chat.load_character, [shared.gradio[k] for k in ['instruction_template', 'name1', 'name2', 'mode']], [shared.gradio[k] for k in ['name1', 'name2', 'character_picture', 'greeting', 'context', 'end_of_turn', 'display']]).then(
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chat.redraw_html, reload_inputs, shared.gradio['display'])
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shared.gradio['upload_chat_history'].upload(
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@ -784,6 +786,7 @@ def create_interface():
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shared.gradio['your_picture'].change(chat.upload_your_profile_picture, [shared.gradio[k] for k in ['your_picture', 'name1', 'name2', 'mode']], shared.gradio['display'])
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shared.gradio['interface'].load(None, None, None, _js=f"() => {{{ui.main_js+ui.chat_js}}}")
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shared.gradio['interface'].load(chat.load_character, [shared.gradio[k] for k in ['instruction_template', 'name1', 'name2', 'mode']], [shared.gradio[k] for k in ['name1', 'name2', 'character_picture', 'greeting', 'context', 'end_of_turn', 'display']])
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shared.gradio['interface'].load(chat.load_default_history, [shared.gradio[k] for k in ['name1', 'name2']], None)
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shared.gradio['interface'].load(chat.redraw_html, reload_inputs, shared.gradio['display'], show_progress=True)
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@ -12,6 +12,7 @@
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"stop_at_newline": false,
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"add_bos_token": true,
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"ban_eos_token": false,
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"skip_special_tokens": true,
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"truncation_length": 2048,
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"truncation_length_min": 0,
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"truncation_length_max": 4096,
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