Update README.md

README.md

@@ -3,197 +3,56 @@ library_name: transformers
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-# Model Card for Model ID
+# Finetuned Mistral 7B model on philosophical texts
 
-<!-- Provide a quick summary of what the model is/does. -->
+This model is a finetune of `mistralai/Mistral-7B-Instruct-v0.3`. It was tuned with the Stanford Encyclopedia of Philosophy (SEP) from here: `AiresPucrs/stanford-encyclopedia-philosophy`
 
+Before fine-tuning:
+The Allegory of the Cave is a philosophical thought experiment by Plato, presented in his work The Republic. In this allegory, Plato describes a group of people who have lived chained in a dark cave since birth, with their backs facing a wall on which shadows are projected from objects passing in front of a fire behind them. These prisoners believe that the shadows they see are reality itself. One prisoner is freed and leaves the cave, eventually coming to understand that the shadows are mere representations of real things outside the cave. He returns to the cave to try to enlighten the other prisoners about the true nature of reality, but they reject his claims because they cannot conceive of anything beyond what they can perceive through their senses.
 
+Plato uses this allegory to illustrate the idea that our understanding of the world is limited by our sensory experiences and that we must strive for knowledge and wisdom in order to truly comprehend reality. It also highlights the difficulty in communicating abstract ideas to those who have not experienced them firsthand.
 
-## Model Details
+After finetuning: 
+In Plato’s Allegory of the Cave, a philosopher compares human beings who live in a cave and are chained so that they can only see shadows on the wall to people who have been educated by philosophy. The philosopher says that the prisoners in the cave represent those who have not been educated by philosophy, while the free person represents someone who has been educated by philosophy. According to the philosopher, the prisoners in the cave are like people who do not understand what is real because all they know is the world of appearances (the shadows). The philosopher argues that the prisoners need to be freed from their chains and led out into the sunlight where they will see the sun itself instead of just its reflection on the walls of the cave. This is similar to how philosophers argue that we should try to understand reality as it really is rather than just accepting our everyday perceptions of things. The philosopher also suggests that the process of being freed from the chains and seeing the sun for the first time is painful, but necessary if one wants to truly understand reality.
 
-### Model Description
 
-<!-- Provide a longer summary of what this model is. -->
+## Using the model
 
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
+To load the model, you can apply the adapter straight to the original base model: 
 
-- **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]
+```python
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
 
-### Model Sources [optional]
+base_model_id = "mistralai/Mistral-7B-Instruct-v0.3"
+bnb_config = BitsAndBytesConfig(
+    load_in_4bit=True,
+    bnb_4bit_use_double_quant=True,
+    bnb_4bit_quant_type="nf4",
+    bnb_4bit_compute_dtype=torch.bfloat16
+)
 
-<!-- Provide the basic links for the model. -->
+base_model = AutoModelForCausalLM.from_pretrained(
+    base_model_id,  # Mistral, same as before
+    quantization_config=bnb_config,  # Same quantization config as before
+    device_map="auto",
+    trust_remote_code=True,
+)
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+tokenizer = AutoTokenizer.from_pretrained(base_model_id, add_bos_token=True, trust_remote_code=True)
 
-## Uses
+prompt = "Please explain the allegory of the cave to me."
+model_input = eval_tokenizer(prompt, return_tensors="pt").to("cuda")
 
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+ft_model.eval()
+with torch.no_grad():
+    print(eval_tokenizer.decode(ft_model.generate(**model_input, max_new_tokens=256, repetition_penalty=1.15)[0], skip_special_tokens=True))
+```
 
-### Direct Use
 
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+## Sources
 
-[More Information Needed]
+Base model: https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3
+Dataset for finetuning: https://huggingface.co/datasets/AiresPucrs/stanford-encyclopedia-philosophy
 
-### 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. -->
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-[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
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-[More Information Needed]
-
-#### Hardware
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-[More Information Needed]
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-#### Software
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-[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:**
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-[More Information Needed]
-
-**APA:**
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-[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]
+I hold no rights to the base model or the dataset used.