Upload Medical-Mixtral-7B-v2k

README.md

@@ -3,50 +3,200 @@ library_name: peft
 base_model: mistralai/Mistral-7B-Instruct-v0.2
 ---
 
-# Medical-Mixtral-7B-v2k
+# Model Card for Model ID
 
-## Description
-Fine-tuned Mixtral model for answering medical assistance questions. This model is a novel version of mistralai/Mixtral-8x7B-Instruct-v0.1, adapted to a subset of 2.0k records from the AI Medical Chatbot dataset, which contains 250k records (https://huggingface.co/datasets/ruslanmv/ai-medical-chatbot). The purpose of this model is to provide a ready chatbot to answer questions related to medical assistance.
+<!-- Provide a quick summary of what the model is/does. -->
 
-## Intended Use
-This model is intended for providing assistance and answering questions related to medical inquiries. It is suitable for use in chatbot applications where users seek medical advice, information, or assistance.
 
-## Example Usage
-```python
 
-from transformers import AutoModelForCausalLM, AutoTokenizer
+## Model Details
 
-# Define the name of your fine-tuned model
-finetuned_model = 'ruslanmv/Medical-Mixtral-7B-v2k'
+### Model Description
 
-# Load tokenizer
-tokenizer = AutoTokenizer.from_pretrained(finetuned_model, trust_remote_code=True)
+<!-- Provide a longer summary of what this model is. -->
 
-# Load the model with the provided adapter configuration and weights
-model_pretrained = AutoModelForCausalLM.from_pretrained(finetuned_model, trust_remote_code=True, torch_dtype=torch.float16)
 
-messages = [
-    {'role': 'user', 'content': 'What should I do to reduce my weight gained due to genetic hypothyroidism?'},
-    {'role': 'assistant', 'content': ''},
-]
 
-input_ids = tokenizer.apply_chat_template(messages, return_tensors='pt').to('cuda')
-outputs = model_pretrained.generate(input_ids, max_new_tokens=500)
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
 
-print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+### Model Sources [optional]
 
-```
-## Training Data
-- **Dataset Name:** AI Medical Chatbot
-- **Dataset URL:** https://huggingface.co/datasets/ruslanmv/ai-medical-chatbot
-- **Dataset Size:** 250k records
-- **Subset Used:** 2.0k records
+<!-- Provide the basic links for the model. -->
 
-## Limitations
-The model's performance may vary depending on the complexity and specificity of the medical questions.
-The model may not provide accurate answers for every medical query, and users should consult medical professionals for critical healthcare concerns.
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
 
-## Ethical Considerations
-Users should be informed that the model's responses are generated based on patterns in the training data and may not always be accurate or suitable for medical decision-making.
-The model should not be used as a replacement for professional medical advice or diagnosis.
-Sensitive patient data should not be shared with the model, and user privacy should be protected.
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- 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. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+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).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.10.0

adapter_config.json

@@ -20,11 +20,11 @@
   "rank_pattern": {},
   "revision": null,
   "target_modules": [
-    "gate_proj",
     "q_proj",
     "k_proj",
-    "o_proj",
-    "v_proj"
+    "v_proj",
+    "gate_proj",
+    "o_proj"
   ],
   "task_type": "CAUSAL_LM",
   "use_dora": false,

adapter_model.safetensors

@@ -1,3 +1,3 @@
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