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README.md CHANGED
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- ---
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- license: apache-2.0
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: apache-2.0
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+ datasets:
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+ - huihui-ai/FineQwQ-142k
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+ base_model:
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+ - huihui-ai/MicroThinker-3B-Preview
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+ tags:
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+ - llama3.2
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+ - abliterated
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+ - uncensored
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+ library_name: transformers
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+ pipeline_tag: text-generation
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+ language:
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+ - en
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+ ---
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+ # MicroThinker-3B-Preview-v2
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+
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+ MicroThinker-3B-Preview-v2, a new model fine-tuned from the [huihui-ai/MicroThinker-3B-Preview](https://huggingface.co/huihui-ai/MicroThinker-3B-Preview) model, focused on advancing AI reasoning capabilities.
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+ This model is superior to the [huihui-ai/MicroThinker-3B-Preview](https://huggingface.co/huihui-ai/MicroThinker-3B-Preview) model.
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+
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+ ## Use with ollama
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+
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+ You can use [huihui_ai/microthinker2](https://ollama.com/huihui_ai/microthinker2) directly
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+ ```
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+ ollama run huihui_ai/microthinker2:3b
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+ ```
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+
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+ ## Training Details
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+
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+ This is just a test, but the performance is quite good.
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+
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+ Now, I'll introduce the test environment.
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+
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+ The model was trained using 1 RTX 4090 GPU(24GB) .
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+
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+ The fine-tuning process used 142k from the FineQwQ-142k dataset, max_length(tokens) 21710, quant_bits 4.
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+
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+ The [SFT (Supervised Fine-Tuning)](https://github.com/modelscope/ms-swift) process is divided into several steps, and no code needs to be written.
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+ 1. Create the environment.
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+
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+ ```
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+ conda create -yn ms-swift python=3.11
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+ conda activate ms-swift
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+
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+ git clone https://github.com/modelscope/ms-swift.git
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+
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+ cd ms-swift
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+ pip install -e .
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+ cd ..
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+ ```
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+
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+
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+ 2. Download the model and dataset.
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+
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+ ```
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+ huggingface-cli download huihui-ai/MicroThinker-3B-Preview --local-dir ./huihui-ai/MicroThinker-3B-Preview
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+ huggingface-cli download --repo-type dataset huihui-ai/FineQwQ-142k --local-dir ./data/FineQwQ-142k
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+ ```
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+
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+
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+ 3. Used only the huihui-ai/FineQwQ-142k, Trained for 1 epoch:
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+
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+ ```
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+ swift sft --model huihui-ai/MicroThinker-3B-Preview --model_type llama3_2 --train_type lora --dataset "data/FineQwQ-142k/FineQwQ-142k.jsonl" --num_train_epochs 1 --per_device_train_batch_size 1 --per_device_eval_batch_size 1 --max_length 21710 --quant_bits 4 --bnb_4bit_compute_dtype bfloat16 --bnb_4bit_quant_storage bfloat16 --lora_rank 8 --lora_alpha 32 --gradient_checkpointing true --weight_decay 0.1 --learning_rate 1e-4 --gradient_accumulation_steps 16 --eval_steps 500 --save_steps 500 --logging_steps 100 --system "You are a helpful assistant. You should think step-by-step." --output_dir output/MicroThinker-3B-Preview/lora/sft2 --model_author "huihui-ai" --model_name "MicroThinker-3B-Preview"
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+ ```
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+
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+ 4. Save the final fine-tuned model. After you're done, input `exit` to exit.
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+ Replace the directories below with specific ones.
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+
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+ ```
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+ swift infer --model huihui-ai/MicroThinker-3B-Preview --model_type llama3_2 --adapters output/MicroThinker-3B-Preview/lora/sft2/v2-20250110-180322\checkpoint-8786 --stream true --infer_backend pt --max_new_tokens 2048 --merge_lora true
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+ ```
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+
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+
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+ This should create a new model directory: `checkpoint-8786-merged`, Rename the directory to `MicroThinker-3B-Preview-v2`, Copy or move this directory to the `huihui` directory.
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+
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+ 5. Perform inference on the final fine-tuned model.
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+
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+ ```
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+ swift infer --model huihui/MicroThinker-3B-Preview-v2 --stream true --infer_backend pt --max_new_tokens 8192
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+ ```
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+
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+ 6. Test examples.
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+
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+ ```
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+ How many 'r' characters are there in the word "strawberry"?
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+ ```
USE_POLICY.md ADDED
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+ **Llama 3.2** **Acceptable Use Policy**
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+
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+ Meta is committed to promoting safe and fair use of its tools and features, including Llama 3.2. If you access or use Llama 3.2, you agree to this Acceptable Use Policy (“**Policy**”). The most recent copy of this policy can be found at [https://www.llama.com/llama3_2/use-policy](https://www.llama.com/llama3_2/use-policy).
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+
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+ **Prohibited Uses**
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+
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+ We want everyone to use Llama 3.2 safely and responsibly. You agree you will not use, or allow others to use, Llama 3.2 to:
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+
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+
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+
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+ 1. Violate the law or others’ rights, including to:
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+ 1. Engage in, promote, generate, contribute to, encourage, plan, incite, or further illegal or unlawful activity or content, such as:
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+ 1. Violence or terrorism
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+ 2. Exploitation or harm to children, including the solicitation, creation, acquisition, or dissemination of child exploitative content or failure to report Child Sexual Abuse Material
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+ 3. Human trafficking, exploitation, and sexual violence
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+ 4. The illegal distribution of information or materials to minors, including obscene materials, or failure to employ legally required age-gating in connection with such information or materials.
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+ 5. Sexual solicitation
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+ 6. Any other criminal activity
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+ 1. Engage in, promote, incite, or facilitate the harassment, abuse, threatening, or bullying of individuals or groups of individuals
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+ 2. Engage in, promote, incite, or facilitate discrimination or other unlawful or harmful conduct in the provision of employment, employment benefits, credit, housing, other economic benefits, or other essential goods and services
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+ 3. Engage in the unauthorized or unlicensed practice of any profession including, but not limited to, financial, legal, medical/health, or related professional practices
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+ 4. Collect, process, disclose, generate, or infer private or sensitive information about individuals, including information about individuals’ identity, health, or demographic information, unless you have obtained the right to do so in accordance with applicable law
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+ 5. Engage in or facilitate any action or generate any content that infringes, misappropriates, or otherwise violates any third-party rights, including the outputs or results of any products or services using the Llama Materials
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+ 6. Create, generate, or facilitate the creation of malicious code, malware, computer viruses or do anything else that could disable, overburden, interfere with or impair the proper working, integrity, operation or appearance of a website or computer system
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+ 7. Engage in any action, or facilitate any action, to intentionally circumvent or remove usage restrictions or other safety measures, or to enable functionality disabled by Meta 
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+ 2. Engage in, promote, incite, facilitate, or assist in the planning or development of activities that present a risk of death or bodily harm to individuals, including use of Llama 3.2 related to the following:
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+ 8. Military, warfare, nuclear industries or applications, espionage, use for materials or activities that are subject to the International Traffic Arms Regulations (ITAR) maintained by the United States Department of State or to the U.S. Biological Weapons Anti-Terrorism Act of 1989 or the Chemical Weapons Convention Implementation Act of 1997
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+ 9. Guns and illegal weapons (including weapon development)
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+ 10. Illegal drugs and regulated/controlled substances
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+ 11. Operation of critical infrastructure, transportation technologies, or heavy machinery
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+ 12. Self-harm or harm to others, including suicide, cutting, and eating disorders
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+ 13. Any content intended to incite or promote violence, abuse, or any infliction of bodily harm to an individual
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+ 3. Intentionally deceive or mislead others, including use of Llama 3.2 related to the following:
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+ 14. Generating, promoting, or furthering fraud or the creation or promotion of disinformation
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+ 15. Generating, promoting, or furthering defamatory content, including the creation of defamatory statements, images, or other content
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+ 16. Generating, promoting, or further distributing spam
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+ 17. Impersonating another individual without consent, authorization, or legal right
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+ 18. Representing that the use of Llama 3.2 or outputs are human-generated
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+ 19. Generating or facilitating false online engagement, including fake reviews and other means of fake online engagement 
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+ 4. Fail to appropriately disclose to end users any known dangers of your AI system
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+ 5. Interact with third party tools, models, or software designed to generate unlawful content or engage in unlawful or harmful conduct and/or represent that the outputs of such tools, models, or software are associated with Meta or Llama 3.2
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+
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+ With respect to any multimodal models included in Llama 3.2, the rights granted under Section 1(a) of the Llama 3.2 Community License Agreement are not being granted to you if you are an individual domiciled in, or a company with a principal place of business in, the European Union. This restriction does not apply to end users of a product or service that incorporates any such multimodal models.
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+
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+ Please report any violation of this Policy, software “bug,” or other problems that could lead to a violation of this Policy through one of the following means:
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+
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+
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+
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+ * Reporting issues with the model: [https://github.com/meta-llama/llama-models/issues](https://l.workplace.com/l.php?u=https%3A%2F%2Fgithub.com%2Fmeta-llama%2Fllama-models%2Fissues&h=AT0qV8W9BFT6NwihiOHRuKYQM_UnkzN_NmHMy91OT55gkLpgi4kQupHUl0ssR4dQsIQ8n3tfd0vtkobvsEvt1l4Ic6GXI2EeuHV8N08OG2WnbAmm0FL4ObkazC6G_256vN0lN9DsykCvCqGZ)
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+ * Reporting risky content generated by the model: [developers.facebook.com/llama_output_feedback](http://developers.facebook.com/llama_output_feedback)
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+ * Reporting bugs and security concerns: [facebook.com/whitehat/info](http://facebook.com/whitehat/info)
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+ * Reporting violations of the Acceptable Use Policy or unlicensed uses of Llama 3.2: [email protected]
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+ },
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+ },
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+ }
2051
+ },
2052
+ "bos_token": "<|begin_of_text|>",
2053
+ "chat_template": "{{- bos_token }}\n{%- if custom_tools is defined %}\n {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n {%- set tools_in_user_message = true %}\n{%- endif %}\n{%- if not date_string is defined %}\n {%- if strftime_now is defined %}\n {%- set date_string = strftime_now(\"%d %b %Y\") %}\n {%- else %}\n {%- set date_string = \"26 Jul 2024\" %}\n {%- endif %}\n{%- endif %}\n{%- if not tools is defined %}\n {%- set tools = none %}\n{%- endif %}\n\n{#- This block extracts the system message, so we can slot it into the right place. #}\n{%- if messages[0]['role'] == 'system' %}\n {%- set system_message = messages[0]['content']|trim %}\n {%- set messages = messages[1:] %}\n{%- else %}\n {%- set system_message = \"\" %}\n{%- endif %}\n\n{#- System message #}\n{{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n{%- if tools is not none %}\n {{- \"Environment: ipython\\n\" }}\n{%- endif %}\n{{- \"Cutting Knowledge Date: December 2023\\n\" }}\n{{- \"Today Date: \" + date_string + \"\\n\\n\" }}\n{%- if tools is not none and not tools_in_user_message %}\n {{- \"You have access to the following functions. To call a function, please respond with JSON for a function call.\" }}\n {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n {{- \"Do not use variables.\\n\\n\" }}\n {%- for t in tools %}\n {{- t | tojson(indent=4) }}\n {{- \"\\n\\n\" }}\n {%- endfor %}\n{%- endif %}\n{{- system_message }}\n{{- \"<|eot_id|>\" }}\n\n{#- Custom tools are passed in a user message with some extra guidance #}\n{%- if tools_in_user_message and not tools is none %}\n {#- Extract the first user message so we can plug it in here #}\n {%- if messages | length != 0 %}\n {%- set first_user_message = messages[0]['content']|trim %}\n {%- set messages = messages[1:] %}\n {%- else %}\n {{- raise_exception(\"Cannot put tools in the first user message when there's no first user message!\") }}\n{%- endif %}\n {{- '<|start_header_id|>user<|end_header_id|>\\n\\n' -}}\n {{- \"Given the following functions, please respond with a JSON for a function call \" }}\n {{- \"with its proper arguments that best answers the given prompt.\\n\\n\" }}\n {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n {{- \"Do not use variables.\\n\\n\" }}\n {%- for t in tools %}\n {{- t | tojson(indent=4) }}\n {{- \"\\n\\n\" }}\n {%- endfor %}\n {{- first_user_message + \"<|eot_id|>\"}}\n{%- endif %}\n\n{%- for message in messages %}\n {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}\n {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\\n\\n'+ message['content'] | trim + '<|eot_id|>' }}\n {%- elif 'tool_calls' in message %}\n {%- if not message.tool_calls|length == 1 %}\n {{- raise_exception(\"This model only supports single tool-calls at once!\") }}\n {%- endif %}\n {%- set tool_call = message.tool_calls[0].function %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n {{- '\"parameters\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- \"}\" }}\n {{- \"<|eot_id|>\" }}\n {%- elif message.role == \"tool\" or message.role == \"ipython\" %}\n {{- \"<|start_header_id|>ipython<|end_header_id|>\\n\\n\" }}\n {%- if message.content is mapping or message.content is iterable %}\n {{- message.content | tojson }}\n {%- else %}\n {{- message.content }}\n {%- endif %}\n {{- \"<|eot_id|>\" }}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' }}\n{%- endif %}\n",
2054
+ "clean_up_tokenization_spaces": true,
2055
+ "eos_token": "<|eot_id|>",
2056
+ "extra_special_tokens": {},
2057
+ "max_length": null,
2058
+ "model_input_names": [
2059
+ "input_ids",
2060
+ "attention_mask"
2061
+ ],
2062
+ "model_max_length": 131072,
2063
+ "pad_to_multiple_of": null,
2064
+ "pad_token": "<|eot_id|>",
2065
+ "pad_token_type_id": 0,
2066
+ "padding_side": "left",
2067
+ "tokenizer_class": "PreTrainedTokenizerFast"
2068
+ }