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.gitattributes CHANGED
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README.md ADDED
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+ ---
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+ base_model: Qwen/Qwen2.5-Coder-14B-Instruct
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+ library_name: peft
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+ model_name: qwen_text2sql_sft_lora
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+ tags:
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+ - base_model:adapter:Qwen/Qwen2.5-Coder-14B-Instruct
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+ - lora
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+ - sft
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+ - transformers
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+ - trl
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+ licence: license
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+ pipeline_tag: text-generation
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+ ---
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+
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+ # Model Card for qwen_text2sql_sft_lora
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+
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+ This model is a fine-tuned version of [Qwen/Qwen2.5-Coder-14B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-14B-Instruct).
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+ It has been trained using [TRL](https://github.com/huggingface/trl).
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+
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+ ## Quick start
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+
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+ ```python
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+ from transformers import pipeline
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+
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+ question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
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+ generator = pipeline("text-generation", model="None", device="cuda")
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+ output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
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+ print(output["generated_text"])
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+ ```
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+
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+ ## Training procedure
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+
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+
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+
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+
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+
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+ This model was trained with SFT.
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+
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+ ### Framework versions
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+
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+ - PEFT 0.19.1
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+ - TRL: 1.3.0
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+ - Transformers: 5.8.0
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+ - Pytorch: 2.10.0+cu128
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+ - Datasets: 4.8.5
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+ - Tokenizers: 0.22.2
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+
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+ ## Citations
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+
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+
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+
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+ Cite TRL as:
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+
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+ ```bibtex
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+ @software{vonwerra2020trl,
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+ title = {{TRL: Transformers Reinforcement Learning}},
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+ author = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
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+ license = {Apache-2.0},
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+ url = {https://github.com/huggingface/trl},
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+ year = {2020}
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+ }
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+ ```
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+ "inference_mode": true,
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+ "init_lora_weights": true,
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+ "megatron_core": "megatron.core",
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+ "peft_type": "LORA",
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+ "peft_version": "0.19.1",
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+ "qalora_group_size": 16,
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+ "r": 32,
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+ "rank_pattern": {},
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+ "revision": null,
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+ "target_modules": [
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+ "k_proj",
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+ "up_proj",
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+ "o_proj",
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+ "gate_proj",
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+ "target_parameters": null,
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+ "task_type": "CAUSAL_LM",
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+ "trainable_token_indices": null,
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+ "use_bdlora": null,
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+ "use_dora": false,
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+ "use_qalora": false,
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+ "use_rslora": false
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+ }
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+ {%- if tools %}
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+ {{- '<|im_start|>system\n' }}
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+ {%- if messages[0]['role'] == 'system' %}
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+ {{- messages[0]['content'] }}
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+ {%- else %}
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+ {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
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+ {%- endif %}
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+ {{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
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+ {%- for tool in tools %}
10
+ {{- "\n" }}
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+ {{- tool | tojson }}
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+ {%- endfor %}
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+ {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
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+ {%- else %}
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+ {%- if messages[0]['role'] == 'system' %}
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+ {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
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+ {%- else %}
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+ {{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
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+ {%- endif %}
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+ {%- endif %}
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+ {%- for message in messages %}
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+ {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
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+ {%- elif message.role == "assistant" %}
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+ {%- set tool_call = tool_call.function %}
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+ {{- '\n<tool_call>\n{"name": "' }}
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+ {{- tool_call.name }}
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+ {{- '", "arguments": ' }}
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+ {{- tool_call.arguments | tojson }}
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+ {{- '}\n</tool_call>' }}
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+ {%- endfor %}
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+ {%- elif message.role == "tool" %}
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+ {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
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+ {{- '<|im_start|>user' }}
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+ {{- message.content }}
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+ {{- '\n</tool_response>' }}
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+ {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
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+ {{- '<|im_end|>\n' }}
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+ {{- '<|im_start|>assistant\n' }}
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checkpoint-313/README.md ADDED
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1
+ ---
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+ base_model: Qwen/Qwen2.5-Coder-14B-Instruct
3
+ library_name: peft
4
+ pipeline_tag: text-generation
5
+ tags:
6
+ - base_model:adapter:Qwen/Qwen2.5-Coder-14B-Instruct
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+ - lora
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+ - sft
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+ - transformers
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+ - trl
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+ ---
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+
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+ # Model Card for Model ID
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+
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+ <!-- Provide a quick summary of what the model is/does. -->
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+
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+
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+
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+ ## Model Details
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+
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+ ### Model Description
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+
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+ <!-- Provide a longer summary of what this model is. -->
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+
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+
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+
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+ - **Developed by:** [More Information Needed]
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+ - **Funded by [optional]:** [More Information Needed]
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+ - **Shared by [optional]:** [More Information Needed]
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+ - **Model type:** [More Information Needed]
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+ - **Language(s) (NLP):** [More Information Needed]
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+ - **License:** [More Information Needed]
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+ - **Finetuned from model [optional]:** [More Information Needed]
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+
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+ ### Model Sources [optional]
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+
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+ <!-- Provide the basic links for the model. -->
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+
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+ - **Repository:** [More Information Needed]
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+ - **Paper [optional]:** [More Information Needed]
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+ - **Demo [optional]:** [More Information Needed]
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+
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+ ## Uses
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+
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+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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+
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+ ### Direct Use
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+
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+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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+
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+ [More Information Needed]
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+
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+ ### Downstream Use [optional]
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+
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+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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+
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+ [More Information Needed]
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+
59
+ ### Out-of-Scope Use
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+
61
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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+
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+ [More Information Needed]
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+
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+ ## Bias, Risks, and Limitations
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+
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+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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+
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+ [More Information Needed]
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+
71
+ ### Recommendations
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+
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+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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+
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+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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+
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+ ## How to Get Started with the Model
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+
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+ Use the code below to get started with the model.
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+
81
+ [More Information Needed]
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+
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+ ## Training Details
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+
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+ ### Training Data
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+
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+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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+
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+ [More Information Needed]
90
+
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+ ### Training Procedure
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+
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+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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+
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+ #### Preprocessing [optional]
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+
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+ [More Information Needed]
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+
99
+
100
+ #### Training Hyperparameters
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+
102
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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+
104
+ #### Speeds, Sizes, Times [optional]
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+
106
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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+
108
+ [More Information Needed]
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+
110
+ ## Evaluation
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+
112
+ <!-- This section describes the evaluation protocols and provides the results. -->
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+
114
+ ### Testing Data, Factors & Metrics
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+
116
+ #### Testing Data
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+
118
+ <!-- This should link to a Dataset Card if possible. -->
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+
120
+ [More Information Needed]
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+
122
+ #### Factors
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+
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+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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+
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+ [More Information Needed]
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+
128
+ #### Metrics
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+
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+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
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+
132
+ [More Information Needed]
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+
134
+ ### Results
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+
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+ [More Information Needed]
137
+
138
+ #### Summary
139
+
140
+
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+
142
+ ## Model Examination [optional]
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+
144
+ <!-- Relevant interpretability work for the model goes here -->
145
+
146
+ [More Information Needed]
147
+
148
+ ## Environmental Impact
149
+
150
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
151
+
152
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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+
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+ - **Hardware Type:** [More Information Needed]
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+ - **Hours used:** [More Information Needed]
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+ - **Cloud Provider:** [More Information Needed]
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+ - **Compute Region:** [More Information Needed]
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+ - **Carbon Emitted:** [More Information Needed]
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+
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+ ## Technical Specifications [optional]
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+
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+ ### Model Architecture and Objective
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+
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+ [More Information Needed]
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+
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+ ### Compute Infrastructure
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+
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+ [More Information Needed]
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+
170
+ #### Hardware
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+
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+ [More Information Needed]
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+
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+ #### Software
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+
176
+ [More Information Needed]
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+
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+ ## Citation [optional]
179
+
180
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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+
182
+ **BibTeX:**
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+
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+ [More Information Needed]
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+
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+ **APA:**
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+
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+ [More Information Needed]
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+
190
+ ## Glossary [optional]
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+
192
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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+
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+ [More Information Needed]
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+
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+ ## More Information [optional]
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+
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+ [More Information Needed]
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+
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+ ## Model Card Authors [optional]
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+
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+ [More Information Needed]
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+
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+ ## Model Card Contact
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+
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+ [More Information Needed]
207
+ ### Framework versions
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+
209
+ - PEFT 0.19.1
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+ "use_qalora": false,
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+ {{- '<|im_start|>system\n' }}
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+ {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
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+ {{- '<|im_start|>assistant\n' }}
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