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  1. README.md +37 -56
  2. adapter_config.json +4 -4
  3. adapter_model.safetensors +1 -1
README.md CHANGED
@@ -5,8 +5,8 @@ base_model: mistralai/Mistral-7B-v0.1
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  # Model Card for Model ID
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- LoRA model trained for ~11 hours on r/uwaterloo data.
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- Only trained on top-level comments with the most upvotes on each post.
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  ## Model Details
@@ -17,33 +17,49 @@ Only trained on top-level comments with the most upvotes on each post.
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- - **Developed by:** Anthony Susevski and Alvin Li
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- - **Model type:** LoRA
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- - **Language(s) (NLP):** English
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- - **License:** mit
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- - **Finetuned from model [optional]:** mistralai/Mistral-7B-v0.1
 
 
 
 
 
 
 
 
 
 
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  ## Uses
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- Pass a post title and a post text(optional) in the style of a Reddit post into the below prompt.
 
 
 
 
 
 
 
 
 
 
 
 
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- ```
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- prompt = f"""
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- Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
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-
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- ### Instruction:
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- Respond to the reddit post in the style of a University of Waterloo student.
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- ### Input:
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- {post_title}
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- {post_text}
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- ### Response:
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- ```
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  ## Bias, Risks, and Limitations
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- No alignment training as of yet -- only SFT.
 
 
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  ### Recommendations
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@@ -55,42 +71,7 @@ Users (both direct and downstream) should be made aware of the risks, biases and
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  Use the code below to get started with the model.
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- ```
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- from transformers import AutoTokenizer, AutoModelForCausalLM
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- import torch
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- from peft import PeftModel, PeftConfig
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-
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- peft_model_id = "asusevski/mistraloo-sft"
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- peft_config = PeftConfig.from_pretrained(peft_model_id)
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- model = AutoModelForCausalLM.from_pretrained(peft_config.base_model_name_or_path)
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- model = PeftModel.from_pretrained(model, peft_model_id).to(device)
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- model.eval()
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-
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-
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- tokenizer = AutoTokenizer.from_pretrained(
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- peft_config.base_model_name_or_path,
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- add_bos_token=True
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- )
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-
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- post_title = "my example post title"
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- post_text = "my example post text"
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- prompt = f"""
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- Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
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-
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- ### Instruction:
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- Respond to the reddit post in the style of a University of Waterloo student.
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-
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- ### Input:
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- {post_title}
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- {post_text}
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-
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- ### Response:
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- """
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- model_input = tokenizer(prompt, return_tensors="pt").to(device)
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- with torch.no_grad():
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- model_output = model.generate(**model_input, max_new_tokens=256, repetition_penalty=1.15)[0]
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- output = tokenizer.decode(model_output, skip_special_tokens=True)
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- ```
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  ## Training Details
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  # Model Card for Model ID
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+ <!-- Provide a quick summary of what the model is/does. -->
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+
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  ## Model Details
 
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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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  ## Uses
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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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+ ### Out-of-Scope Use
 
 
 
 
 
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+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
 
 
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+ [More Information Needed]
 
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  ## Bias, Risks, and Limitations
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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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  ### Recommendations
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  Use the code below to get started with the model.
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+ [More Information Needed]
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ## Training Details
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adapter_config.json CHANGED
@@ -19,14 +19,14 @@
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  "rank_pattern": {},
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  "revision": null,
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  "target_modules": [
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- "lm_head",
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  "v_proj",
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  "k_proj",
 
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  "o_proj",
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  "q_proj",
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- "gate_proj",
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- "up_proj",
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- "down_proj"
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  ],
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  "task_type": "CAUSAL_LM"
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  }
 
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  "rank_pattern": {},
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  "revision": null,
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  "target_modules": [
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+ "down_proj",
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  "v_proj",
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  "k_proj",
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+ "gate_proj",
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  "o_proj",
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  "q_proj",
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+ "lm_head",
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+ "up_proj"
 
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  ],
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  "task_type": "CAUSAL_LM"
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  }
adapter_model.safetensors CHANGED
@@ -1,3 +1,3 @@
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