rustformers
/

pythia-ggml

@@ -3,200 +3,78 @@ tags:
 - llm-rs
 - ggml
 pipeline_tag: text-generation
 ---
-# Model Card for Model ID
-<!-- Provide a quick summary of what the model is/does. -->
-## Model Details
-### Model Description
-<!-- Provide a longer summary of what this model is. -->
-- **Developed by:** [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 Data 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 Data 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]

 - llm-rs
 - ggml
 pipeline_tag: text-generation
+license: apache-2.0
+language:
+- en
 ---
+# GGML converted versions of [EleutherAI](https://huggingface.co/EleutherAI)'s Pythia models
+## Description:
+The *Pythia Scaling Suite* is a collection of models developed to facilitate
+interpretability research. It contains two sets of eight models of sizes
+70M, 160M, 410M, 1B, 1.4B, 2.8B, 6.9B, and 12B. For each size, there are two
+models: one trained on the Pile, and one trained on the Pile after the dataset
+has been globally deduplicated. All 8 model sizes are trained on the exact
+same data, in the exact same order. We also provide 154 intermediate
+checkpoints per model, hosted on Hugging Face as branches.
+The Pythia model suite was deliberately designed to promote scientific
+research on large language models, especially interpretability research.
+Despite not centering downstream performance as a design goal, we find the
+models match or exceed the performance of
+similar and same-sized models, such as those in the OPT and GPT-Neo suites.
+## Converted Models:
+| Name   | Based on |  Type | Container |
+|-|-|-|-|
+| [pythia-70m-f16.bin](https://huggingface.co/Rustformers/pythia-ggml/blob/main/pythia-70m-f16.bin) |  [Pythia-70M](https://huggingface.co/EleutherAI/pythia-70m) | fp16 | GGML |
+| [pythia-70m-q4_0-ggjt.bin](https://huggingface.co/Rustformers/pythia-ggml/blob/main/pythia-70m-q4_0-ggjt.bin) |  [Pythia-70M](https://huggingface.co/EleutherAI/pythia-70m) | int4 | GGJT |
+| [pythia-70m-q4_0.bin](https://huggingface.co/Rustformers/pythia-ggml/blob/main/pythia-70m-q4_0.bin) |  [Pythia-70M](https://huggingface.co/EleutherAI/pythia-70m) | int4 | GGML |
+| [pythia-160m-f16.bin](https://huggingface.co/Rustformers/pythia-ggml/blob/main/pythia-160m-f16.bin) |  [Pythia-160M](https://huggingface.co/EleutherAI/pythia-160m) | fp16 | GGML |
+| [pythia-160m-q4_0-ggjt.bin](https://huggingface.co/Rustformers/pythia-ggml/blob/main/pythia-160m-q4_0-ggjt.bin) |  [Pythia-160M](https://huggingface.co/EleutherAI/pythia-160m) | int4 | GGJT |
+| [pythia-160m-q4_0.bin](https://huggingface.co/Rustformers/pythia-ggml/blob/main/pythia-160m-q4_0.bin) |  [Pythia-160M](https://huggingface.co/EleutherAI/pythia-160m) | int4 | GGML |
+| [pythia-410m-f16.bin](https://huggingface.co/Rustformers/pythia-ggml/blob/main/pythia-410m-f16.bin) |  [Pythia-410M](https://huggingface.co/EleutherAI/pythia-410m) | fp16 | GGML |
+| [pythia-410m-q4_0-ggjt.bin](https://huggingface.co/Rustformers/pythia-ggml/blob/main/pythia-410m-q4_0-ggjt.bin) |  [Pythia-410M](https://huggingface.co/EleutherAI/pythia-410m) | int4 | GGJT |
+| [pythia-410m-q4_0.bin](https://huggingface.co/Rustformers/pythia-ggml/blob/main/pythia-410m-q4_0.bin) |  [Pythia-410M](https://huggingface.co/EleutherAI/pythia-410m) | int4 | GGML |
+| [pythia-1b-f16.bin](https://huggingface.co/Rustformers/pythia-ggml/blob/main/pythia-1b-f16.bin) |  [Pythia-1B](https://huggingface.co/EleutherAI/pythia-1b) | fp16 | GGML |
+| [pythia-1b-q4_0-ggjt.bin](https://huggingface.co/Rustformers/pythia-ggml/blob/main/pythia-1b-q4_0-ggjt.bin) |  [Pythia-1B](https://huggingface.co/EleutherAI/pythia-1b) | int4 | GGJT |
+| [pythia-1b-q4_0.bin](https://huggingface.co/Rustformers/pythia-ggml/blob/main/pythia-1b-q4_0.bin) |  [Pythia-1B](https://huggingface.co/EleutherAI/pythia-1b) | int4 | GGML |
+| [pythia-1.4b-f16.bin](https://huggingface.co/Rustformers/pythia-ggml/blob/main/pythia-1.4b-f16.bin) |  [Pythia-1.4B](https://huggingface.co/EleutherAI/pythia-1.4b) | fp16 | GGML |
+| [pythia-1.4b-q4_0-ggjt.bin](https://huggingface.co/Rustformers/pythia-ggml/blob/main/pythia-1.4b-q4_0-ggjt.bin) |  [Pythia-1.4B](https://huggingface.co/EleutherAI/pythia-1.4b) | int4 | GGJT |
+| [pythia-1.4b-q4_0.bin](https://huggingface.co/Rustformers/pythia-ggml/blob/main/pythia-1.4b-q4_0.bin) |  [Pythia-1.4B](https://huggingface.co/EleutherAI/pythia-1.4b) | int4 | GGML |
+| [pythia-2.8b-f16.bin](https://huggingface.co/Rustformers/pythia-ggml/blob/main/pythia-2.8b-f16.bin) |  [Pythia-2.8B](https://huggingface.co/EleutherAI/pythia-2.8b) | fp16 | GGML |
+| [pythia-2.8b-q4_0-ggjt.bin](https://huggingface.co/Rustformers/pythia-ggml/blob/main/pythia-2.8b-q4_0-ggjt.bin) |  [Pythia-2.8B](https://huggingface.co/EleutherAI/pythia-2.8b) | int4 | GGJT |
+| [pythia-2.8b-q4_0.bin](https://huggingface.co/Rustformers/pythia-ggml/blob/main/pythia-2.8b-q4_0.bin) |  [Pythia-2.8B](https://huggingface.co/EleutherAI/pythia-2.8b) | int4 | GGML |
+## Usage
+### Python via [llm-rs](https://github.com/LLukas22/llm-rs-python):
+#### Installation
+Via pip: `pip install llm-rs`
+#### Run inference
+```python
+from llm_rs import AutoModel
+#Load the model, define any model you like from the list above as the `model_file`
+model = AutoModel.from_pretrained("Rustformers/pythia-ggml",model_file="pythia-70m-q4_0-ggjt.bin")
+#Generate
+print(model.generate("The meaning of life is"))
+```
+### Rust via [Rustformers/llm](https://github.com/rustformers/llm):
+#### Installation
+```
+git clone --recurse-submodules git@github.com:rustformers/llm.git
+cargo build --release
+```
+#### Run inference
+```
+cargo run --release -- gptneox infer -m path/to/model.bin  -p "Tell me how cool the Rust programming language is:"
+```