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talktoaiZERO

Text Generation
Transformers
Safetensors
GGUF
PEFT
llama
Trained with AutoTrain
text-generation-inference
conversational
Inference Endpoints
Model card Files Community
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  1. .gitattributes +1 -0
  2. LICENSE +20 -0
  3. README.md +51 -3
  4. USE_POLICY.md +51 -0
  5. adapter_config.json +34 -0
  6. adapter_model.safetensors +3 -0
  7. config.json +38 -0
  8. generation_config.json +12 -0
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  14. model.safetensors.index.json +298 -0
  15. special_tokens_map.json +17 -0
  16. talktoaiZERO.gguf +3 -0
  17. tokenizer.json +0 -0
  18. tokenizer_config.json +2063 -0
  19. training_args.bin +3 -0
  20. training_params.json +48 -0
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LICENSE ADDED
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+ # License for talktoaiZERO
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+
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+ This repository is a derivative work based on **Meta-Llama-3.1-8B-Instruct**, which is licensed under the **Llama 2 Community License Agreement**. You must agree to the terms of the original license from Meta Platforms, Inc. before using this model.
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+
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+ ## Meta-Llama 3.1-8B License:
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+ For the original license agreement, please refer to:
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+ [Meta Llama 2 License](https://huggingface.co/meta-llama/Meta-Llama-2-8B/blob/main/LICENSE.md)
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+
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+ ## Derivative Work
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+ The fine-tuning and modifications made to the base model for **talktoaiZERO.gguf** are subject to the **MIT License**. Please review the following terms for this derivative work.
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+
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+ MIT License:
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+
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+ Copyright (c) 2024 [talktoai.org/talktoaiZERO]
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+
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+ Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
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+
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+ The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
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+
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+ THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
README.md CHANGED
@@ -1,3 +1,51 @@
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- ---
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- license: mit
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ tags:
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+ - autotrain
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+ - text-generation-inference
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+ - text-generation
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+ - peft
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+ library_name: transformers
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+ base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
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+ widget:
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+ - messages:
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+ - role: user
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+ content: What are the ethical implications of quantum mechanics in AI systems?
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+ license: other
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+ ---
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+
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+ # talktoaiZERO.gguf - Fine-Tuned with AutoTrain
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+
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+ **talktoaiZERO.gguf** is a fine-tuned version of the **Meta-Llama-3.1-8B-Instruct** model, specifically designed for conversational AI with advanced features in quantum thinking and ethical decision-making. The model was trained using [AutoTrain](https://hf.co/docs/autotrain) and is compatible with **GGUF format**, making it easy to load into WebUIs for text generation and inference.
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+
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+ # Features
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+
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+ - **Base Model**: Meta-Llama-3.1-8B-Instruct
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+ - **Fine-Tuning**: Custom conversational training focused on ethical, quantum-based responses.
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+ - **Use Cases**: Ethical decision-making, advanced conversational AI, and quantum-inspired logic in AI responses.
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+ - **Format**: GGUF (for WebUIs and advanced language models)
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+
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+ # Usage
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+
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+ ```python
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+
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+ model_path = "PATH_TO_THIS_REPO"
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+
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+ tokenizer = AutoTokenizer.from_pretrained(model_path)
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+ model = AutoModelForCausalLM.from_pretrained(
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+ model_path,
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+ device_map="auto",
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+ torch_dtype='auto'
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+ ).eval()
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+
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+ # Sample conversation
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+ messages = [
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+ {"role": "user", "content": "What are the ethical implications of quantum mechanics in AI systems?"}
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+ ]
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+
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+ input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt')
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+ output_ids = model.generate(input_ids.to('cuda'))
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+ response = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=True)
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+
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+ # Model response: "Quantum mechanics introduces complexity, but the goal remains ethical decision-making."
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+ print(response)
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+ # Llama 3.1 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 3.1. If you
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+ access or use Llama 3.1, you agree to this Acceptable Use Policy (“Policy”). The most recent copy of
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+ this policy can be found at [https://llama.meta.com/llama3_1/use-policy](https://llama.meta.com/llama3_1/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 3.1 safely and responsibly. You agree you will not use, or allow
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+ others to use, Llama 3.1 to:
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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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+ 3. Engage in, promote, incite, or facilitate the harassment, abuse, threatening, or bullying of individuals or groups of individuals
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+ 4. 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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+ 5. 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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+ 6. Collect, process, disclose, generate, or infer health, demographic, or other sensitive personal or private information about individuals without rights and consents required by applicable laws
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+ 7. 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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+ 8. 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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+
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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 3.1 related to the following:
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+ 1. 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
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+ 2. Guns and illegal weapons (including weapon development)
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+ 3. Illegal drugs and regulated/controlled substances
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+ 4. Operation of critical infrastructure, transportation technologies, or heavy machinery
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+ 5. Self-harm or harm to others, including suicide, cutting, and eating disorders
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+ 6. Any content intended to incite or promote violence, abuse, or any infliction of bodily harm to an individual
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+
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+ 3. Intentionally deceive or mislead others, including use of Llama 3.1 related to the following:
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+ 1. Generating, promoting, or furthering fraud or the creation or promotion of disinformation
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+ 2. Generating, promoting, or furthering defamatory content, including the creation of defamatory statements, images, or other content
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+ 3. Generating, promoting, or further distributing spam
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+ 4. Impersonating another individual without consent, authorization, or legal right
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+ 5. Representing that the use of Llama 3.1 or outputs are human-generated
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+ 6. Generating or facilitating false online engagement, including fake reviews and other means of fake online engagement
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+
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+ 4. Fail to appropriately disclose to end users any known dangers of your AI system
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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
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+ of this Policy through one of the following means:
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+
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+ * Reporting issues with the model: [https://github.com/meta-llama/llama-models/issues](https://github.com/meta-llama/llama-models/issues)
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+ * Reporting risky content generated by the model: developers.facebook.com/llama_output_feedback
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+ * Reporting bugs and security concerns: facebook.com/whitehat/info
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+ * Reporting violations of the Acceptable Use Policy or unlicensed uses of Llama 3.1: LlamaUseReport@meta.com
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+ "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 {%- set date_string = \"26 Jul 2024\" %}\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 + builtin tools #}\n{{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n{%- if builtin_tools is defined or tools is not none %}\n {{- \"Environment: ipython\\n\" }}\n{%- endif %}\n{%- if builtin_tools is defined %}\n {{- \"Tools: \" + builtin_tools | reject('equalto', 'code_interpreter') | join(\", \") + \"\\n\\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 {%- if builtin_tools is defined and tool_call.name in builtin_tools %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n {{- \"<|python_tag|>\" + tool_call.name + \".call(\" }}\n {%- for arg_name, arg_val in tool_call.arguments | items %}\n {{- arg_name + '=\"' + arg_val + '\"' }}\n {%- if not loop.last %}\n {{- \", \" }}\n {%- endif %}\n {%- endfor %}\n {{- \")\" }}\n {%- else %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n {{- '\"parameters\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- \"}\" }}\n {%- endif %}\n {%- if builtin_tools is defined %}\n {#- This means we're in ipython mode #}\n {{- \"<|eom_id|>\" }}\n {%- else %}\n {{- \"<|eot_id|>\" }}\n {%- endif %}\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,
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+ "eos_token": "<|eot_id|>",
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+ "model_input_names": [
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+ "input_ids",
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+ "attention_mask"
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+ ],
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+ "model_max_length": 2048,
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+ "pad_token": "<|eot_id|>",
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+ "tokenizer_class": "PreTrainedTokenizerFast"
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+ }
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training_params.json ADDED
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+ {
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+ "model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
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+ "project_name": "talktoai",
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+ "data_path": "talktoai/autotrain-data",
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+ "trainer": "sft",
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+ "use_flash_attention_2": false,
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+ "log": "tensorboard",
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+ "disable_gradient_checkpointing": false,
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+ "logging_steps": -1,
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+ "eval_strategy": "epoch",
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+ "save_total_limit": 1,
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+ "auto_find_batch_size": false,
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+ "mixed_precision": "fp16",
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+ "lr": 3e-05,
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+ "epochs": 3,
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+ "batch_size": 2,
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+ "warmup_ratio": 0.1,
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+ "gradient_accumulation": 4,
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+ "optimizer": "adamw_torch",
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+ "scheduler": "linear",
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+ "weight_decay": 0.0,
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+ "max_grad_norm": 1.0,
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+ "seed": 42,
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+ "chat_template": "none",
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+ "quantization": "int4",
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+ "target_modules": "all-linear",
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+ "merge_adapter": false,
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+ "peft": true,
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+ "lora_r": 16,
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+ "lora_alpha": 32,
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+ "lora_dropout": 0.05,
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+ "dpo_beta": 0.1,
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+ "max_prompt_length": 128,
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+ "max_completion_length": null,
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+ "prompt_text_column": "autotrain_prompt",
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+ "text_column": "autotrain_text",
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+ "rejected_text_column": "autotrain_rejected_text",
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+ "push_to_hub": true,
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+ "username": "shafire",
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+ "unsloth": false
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+ }