Update README_TEMPLATE.md

README_TEMPLATE.md

@@ -1,83 +1,32 @@
 ---
-license: bigscience-bloom-rail-1.0
+license: apache-2.0
 language:
-- ak
-- ar
-- as
-- bm
-- bn
-- ca
-- code
 - en
-- es
-- eu
-- fon
-- fr
-- gu
-- hi
-- id
-- ig
-- ki
-- kn
-- lg
-- ln
-- ml
-- mr
-- ne
-- nso
-- ny
-- or
-- pa
-- pt
-- rn
-- rw
-- sn
-- st
-- sw
-- ta
-- te
-- tn
-- ts
-- tum
-- tw
-- ur
-- vi
-- wo
-- xh
-- yo
-- zh
-- zu
-programming_language: 
-- C
-- C++
-- C#
-- Go
-- Java
-- JavaScript
-- Lua
-- PHP
-- Python
-- Ruby
-- Rust
-- Scala
-- TypeScript
+pipeline_tag: text-generation
 tags:
 - llm-rs
 - ggml
-pipeline_tag: text-generation
+datasets:
+- mc4
+- c4
+- togethercomputer/RedPajama-Data-1T
+- bigcode/the-stack
+- allenai/s2orc
+inference: false
 ---
+# GGML converted versions of [Mosaic's](https://huggingface.co/mosaicml) MPT Models
 
-# GGML covnerted Models of [BigScience](https://huggingface.co/bigscience)'s Bloom models
-
-## Description
+MPT-7B is a decoder-style transformer pretrained from scratch on 1T tokens of English text and code.
+This model was trained by [MosaicML](https://www.mosaicml.com).
 
-BLOOM is an autoregressive Large Language Model (LLM), trained to continue text from a prompt on vast amounts of text data using industrial-scale computational resources. As such, it is able to output coherent text in 46 languages and 13 programming languages that is hardly distinguishable from text written by humans. BLOOM can also be instructed to perform text tasks it hasn't been explicitly trained for, by casting them as text generation tasks.
+MPT-7B is part of the family of MosaicPretrainedTransformer (MPT) models, which use a modified transformer architecture optimized for efficient training and inference. 
 
-
-## Converted Models
+## Converted Models:
 $MODELS$
 
-## Usage
+⚠️Caution⚠️: mpt-7b-storywriter is still under development!
+
+## Usage 
 
 ### Python via [llm-rs](https://github.com/LLukas22/llm-rs-python):
 
@@ -89,13 +38,12 @@ Via pip: `pip install llm-rs`
 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/bloom-ggml",model_file="bloom-3b-q4_0-ggjt.bin")
+model = AutoModel.from_pretrained("rustformers/mpt-7b-ggml",model_file="mpt-7b-q4_0-ggjt.bin")
 
 #Generate
 print(model.generate("The meaning of life is"))
 ```
-
-### Rust via [Rustformers/llm](https://github.com/rustformers/llm): 
+### Rust via [rustformers/llm](https://github.com/rustformers/llm): 
 
 #### Installation
 ```
@@ -106,5 +54,24 @@ cargo build --release
 
 #### Run inference
 ```
-cargo run --release -- bloom infer -m path/to/model.bin  -p "Tell me how cool the Rust programming language is:"
+cargo run --release -- mpt infer -m path/to/model.bin  -p "Tell me how cool the Rust programming language is:"
+```
+
+### C via [GGML](https://github.com/ggerganov/ggml)
+The `GGML` example only supports the ggml container type!
+
+#### Installation
+
+```
+git clone https://github.com/ggerganov/ggml
+cd ggml
+mkdir build && cd build
+cmake ..
+make -j4 mpt
+```
+
+#### Run inference
+
+```
+./bin/mpt -m path/to/model.bin -p "The meaning of life is"
 ```