RichardErkhov/sethuiyer_-_Dr_Samantha-7b-gguf

Quantization made by Richard Erkhov.

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Dr_Samantha-7b - GGUF

• —Model creator: https://huggingface.co/sethuiyer/
• —Original model: https://huggingface.co/sethuiyer/Dr_Samantha-7b/

Original model description: --- language:

• —en
• —zh license: llama2 library_name: transformers tags:
• —llama
• —merge
• —medical datasets:
• —GBaker/MedQA-USMLE-4-options
• —cognitivecomputations/samantha-data
• —shibing624/medical base_model:
• —Severus27/BeingWellllama27b
• —ParthasarathyShanmugam/llama-2-7b-samantha pipeline_tag: text-generation model-index:
• —name: Dr_Samantha-7b results:
• —task: type: text-generation name: Text Generation dataset: name: AI2 Reasoning Challenge (25-Shot) type: ai2arc config: ARC-Challenge split: test args: numfew_shot: 25 metrics:
• —type: accnorm value: 53.84 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/openllmleaderboard?query=sethuiyer/DrSamantha-7b name: Open LLM Leaderboard
• —task: type: text-generation name: Text Generation dataset: name: HellaSwag (10-Shot) type: hellaswag split: validation args: numfewshot: 10 metrics:
• —type: accnorm value: 77.95 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/openllmleaderboard?query=sethuiyer/DrSamantha-7b name: Open LLM Leaderboard
• —task: type: text-generation name: Text Generation dataset: name: MMLU (5-Shot) type: cais/mmlu config: all split: test args: numfewshot: 5 metrics:
• —type: acc value: 47.94 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/openllmleaderboard?query=sethuiyer/Dr_Samantha-7b name: Open LLM Leaderboard
• —task: type: text-generation name: Text Generation dataset: name: TruthfulQA (0-shot) type: truthfulqa config: multiplechoice split: validation args: numfewshot: 0 metrics:
• —type: mc2 value: 45.58 source: url: https://huggingface.co/spaces/HuggingFaceH4/openllmleaderboard?query=sethuiyer/Dr_Samantha-7b name: Open LLM Leaderboard
• —task: type: text-generation name: Text Generation dataset: name: Winogrande (5-shot) type: winogrande config: winograndexl split: validation args: numfew_shot: 5 metrics:
• —type: acc value: 73.56 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/openllmleaderboard?query=sethuiyer/Dr_Samantha-7b name: Open LLM Leaderboard
• —task: type: text-generation name: Text Generation dataset: name: GSM8k (5-shot) type: gsm8k config: main split: test args: numfewshot: 5 metrics:
• —type: acc value: 18.8 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/openllmleaderboard?query=sethuiyer/Dr_Samantha-7b name: Open LLM Leaderboard ---

Dr. Samantha

<p align="center"> <img src="https://huggingface.co/sethuiyer/DrSamantha-7b/resolve/main/drsamanthaanimestylereducedquality.webp" height="256px" alt="SynthIQ"> </p>

Overview

Dr. Samantha is a language model made by merging Severus27/BeingWell_llama2_7b and ParthasarathyShanmugam/llama-2-7b-samantha using mergekit.

Has capabilities of a medical knowledge-focused model (trained on USMLE databases and doctor-patient interactions) with the philosophical, psychological, and relational understanding of the Samantha-7b model.

As both a medical consultant and personal counselor, Dr.Samantha could effectively support both physical and mental wellbeing - important for whole-person care.

Yaml Config

slices:
  - sources:
      - model: Severus27/BeingWell_llama2_7b
        layer_range: [0, 32]
      - model: ParthasarathyShanmugam/llama-2-7b-samantha
        layer_range: [0, 32]

merge_method: slerp
base_model: TinyPixel/Llama-2-7B-bf16-sharded

parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5 # fallback for rest of tensors
tokenizer_source: union

dtype: bfloat16

Prompt Template

Below is an instruction that describes a task. Write a response that appropriately completes the request.

### Instruction:
What is your name?

### Response:
My name is Samantha.

⚡ Quantized models

• —GGUF:https://huggingface.co/TheBloke/Dr_Samantha-7B-GGUF
• —GPTQ: https://huggingface.co/TheBloke/Dr_Samantha-7B-GPTQ
• —AWQ: https://huggingface.co/TheBloke/Dr_Samantha-7B-AWQ

Thanks to TheBloke for making this available!

Dr.Samantha is now available on Ollama. You can use it by running the command ``ollama run stuehieyr/dr_samantha`` in your terminal. If you have limited computing resources, check out this video to learn how to run it on a Google Colab backend.

OpenLLM Leaderboard Performance

Subject-wise Accuracy

Evaluation by GPT-4 across 25 random prompts from ChatDoctor-200k Dataset

Overall Rating: 83.5/100

Pros:

• —Demonstrates extensive medical knowledge through accurate identification of potential causes for various symptoms.
• —Responses consistently emphasize the importance of seeking professional diagnoses and treatments.
• —Advice to consult specialists for certain concerns is well-reasoned.
• —Practical interim measures provided for symptom management in several cases.
• —Consistent display of empathy, support, and reassurance for patients' well-being.
• —Clear and understandable explanations of conditions and treatment options.
• —Prompt responses addressing all aspects of medical inquiries.

Cons:

• —Could occasionally place stronger emphasis on urgency when symptoms indicate potential emergencies.
• —Discussion of differential diagnoses could explore a broader range of less common causes.
• —Details around less common symptoms and their implications need more depth at times.
• —Opportunities exist to gather clarifying details on symptom histories through follow-up questions.
• —Consider exploring full medical histories to improve diagnostic context where relevant.
• —Caution levels and risk factors associated with certain conditions could be underscored more.

Open LLM Leaderboard Evaluation Results

Detailed results can be found here