Upload README.md with huggingface_hub

README.md

@@ -0,0 +1,249 @@
+---
+base_model: lamm-mit/Bioinspired-Phi-3-mini-4k
+inference: false
+language:
+- en
+library_name: transformers
+model_creator: lamm-mit
+model_name: Bioinspired-Phi-3-mini-4k
+pipeline_tag: text-generation
+quantized_by: afrideva
+tags:
+- biology
+- materials science
+- code
+- scientific AI
+- biological materials
+- bioinspiration
+- machine learning
+- generative
+- gguf
+- ggml
+- quantized
+- q2_k
+- q3_k_m
+- q4_k_m
+- q5_k_m
+- q6_k
+- q8_0
+---
+# lamm-mit/Bioinspired-Phi-3-mini-4k-GGUF
+
+Quantized GGUF model files for [Bioinspired-Phi-3-mini-4k](https://huggingface.co/lamm-mit/Bioinspired-Phi-3-mini-4k) from [lamm-mit](https://huggingface.co/lamm-mit)
+
+
+| Name | Quant method | Size |
+| ---- | ---- | ---- |
+| [bioinspired-phi-3-mini-4k.fp16.gguf](https://huggingface.co/afrideva/Bioinspired-Phi-3-mini-4k-GGUF/resolve/main/bioinspired-phi-3-mini-4k.fp16.gguf) | fp16 | 7.64 GB  |
+| [bioinspired-phi-3-mini-4k.q2_k.gguf](https://huggingface.co/afrideva/Bioinspired-Phi-3-mini-4k-GGUF/resolve/main/bioinspired-phi-3-mini-4k.q2_k.gguf) | q2_k | 1.42 GB  |
+| [bioinspired-phi-3-mini-4k.q3_k_m.gguf](https://huggingface.co/afrideva/Bioinspired-Phi-3-mini-4k-GGUF/resolve/main/bioinspired-phi-3-mini-4k.q3_k_m.gguf) | q3_k_m | 1.96 GB  |
+| [bioinspired-phi-3-mini-4k.q4_k_m.gguf](https://huggingface.co/afrideva/Bioinspired-Phi-3-mini-4k-GGUF/resolve/main/bioinspired-phi-3-mini-4k.q4_k_m.gguf) | q4_k_m | 2.39 GB  |
+| [bioinspired-phi-3-mini-4k.q5_k_m.gguf](https://huggingface.co/afrideva/Bioinspired-Phi-3-mini-4k-GGUF/resolve/main/bioinspired-phi-3-mini-4k.q5_k_m.gguf) | q5_k_m | 2.82 GB  |
+| [bioinspired-phi-3-mini-4k.q6_k.gguf](https://huggingface.co/afrideva/Bioinspired-Phi-3-mini-4k-GGUF/resolve/main/bioinspired-phi-3-mini-4k.q6_k.gguf) | q6_k | 3.14 GB  |
+| [bioinspired-phi-3-mini-4k.q8_0.gguf](https://huggingface.co/afrideva/Bioinspired-Phi-3-mini-4k-GGUF/resolve/main/bioinspired-phi-3-mini-4k.q8_0.gguf) | q8_0 | 4.06 GB  |
+
+
+
+## Original Model Card:
+# BioinspiredLLM: Conversational Large Language Model for the Mechanics of Biological and Bio-Inspired Materials
+
+Reference: R. Luu and M.J. Buehler, "BioinspiredLLM: Conversational Large Language Model for the Mechanics of Biological and Bio-Inspired Materials," Adv. Science, 2023, DOI: https://doi.org/10.1002/advs.202306724
+
+Abstract: The study of biological materials and bio-inspired materials science is well established; however, surprisingly little knowledge is systematically translated to engineering solutions. To accelerate discovery and guide insights, an open-source autoregressive transformer large language model (LLM), BioinspiredLLM, is reported. The model is finetuned with a corpus of over a thousand peer-reviewed articles in the field of structural biological and bio-inspired materials and can be prompted to recall information, assist with research tasks, and function as an engine for creativity. The model has proven that it is able to accurately recall information about biological materials and is further strengthened with enhanced reasoning ability, as well as with Retrieval-Augmented Generation (RAG) to incorporate new data during generation that can also help to traceback sources, update the knowledge base, and connect knowledge domains. BioinspiredLLM also has shown to develop sound hypotheses regarding biological materials design and remarkably so for materials that have never been explicitly studied before. Lastly, the model shows impressive promise in collaborating with other generative artificial intelligence models in a workflow that can reshape the traditional materials design process. This collaborative generative artificial intelligence method can stimulate and enhance bio-inspired materials design workflows. Biological materials are at a critical intersection of multiple scientific fields and models like BioinspiredLLM help to connect knowledge domains. 
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/623ce1c6b66fedf374859fe7/Xdp_nCYiF2IAPamG5ffIC.png)
+
+# Model Card for Model ID
+
+Fine-tuned LLM with domain knowledge in biological materials, mechanics of materials, modeling and simulation, and related fields. 
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
+
+- **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]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## 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]