Upload README.md

README.md

@@ -48,8 +48,6 @@ tags:
 
 This repo contains GPTQ model files for [Microsoft's Phi 2](https://huggingface.co/microsoft/phi-2).
 
-**NOTE** These GPTQs will only work with Transformers, and require `trust_remote_code=True`.
-
 Multiple GPTQ parameter permutations are provided; see Provided Files below for details of the options provided, their parameters, and the software used to create them.
 
 <!-- description end -->
@@ -57,6 +55,7 @@ Multiple GPTQ parameter permutations are provided; see Provided Files below for
 ## Repositories available
 
 * [GPTQ models for GPU inference, with multiple quantisation parameter options.](https://huggingface.co/TheBloke/phi-2-GPTQ)
+* [2, 3, 4, 5, 6 and 8-bit GGUF models for CPU+GPU inference](https://huggingface.co/TheBloke/phi-2-GGUF)
 * [Microsoft's original unquantised fp16 model in pytorch format, for GPU inference and for further conversions](https://huggingface.co/microsoft/phi-2)
 <!-- repositories-available end -->
 
@@ -95,7 +94,7 @@ Multiple quantisation parameters are provided, to allow you to choose the best o
 
 Each separate quant is in a different branch.  See below for instructions on fetching from different branches.
 
-These GPTQs were made with Transformers.
+Most GPTQ files are made with AutoGPTQ. Mistral models are currently made with Transformers.
 
 <details>
   <summary>Explanation of GPTQ parameters</summary>
@@ -112,12 +111,12 @@ These GPTQs were made with Transformers.
 
 | Branch | Bits | GS | Act Order | Damp % | GPTQ Dataset | Seq Len | Size | ExLlama | Desc |
 | ------ | ---- | -- | --------- | ------ | ------------ | ------- | ---- | ------- | ---- |
-| main | 4 | 128 | Yes | 0.1 | [VMware Open Instruct](https://huggingface.co/datasets/VMware/open-instruct/viewer/) | 2048 | 1.84 GB | No | 4-bit, with Act Order and group size 128g. Uses even less VRAM than 64g, but with slightly lower accuracy. | 
-| gptq-4bit-32g-actorder_True | 4 | 32 | Yes | 0.1 | [VMware Open Instruct](https://huggingface.co/datasets/VMware/open-instruct/viewer/) | 2048 | 1.98 GB | No | 4-bit, with Act Order and group size 32g. Gives highest possible inference quality, with maximum VRAM usage. | 
-| gptq-8bit--1g-actorder_True | 8 | None | Yes | 0.1 | [VMware Open Instruct](https://huggingface.co/datasets/VMware/open-instruct/viewer/) | 2048 | 3.05 GB | No | 8-bit, with Act Order. No group size, to lower VRAM requirements. | 
-| gptq-8bit-128g-actorder_True | 8 | 128 | Yes | 0.1 | [VMware Open Instruct](https://huggingface.co/datasets/VMware/open-instruct/viewer/) | 2048 | 3.10 GB | No | 8-bit, with group size 128g for higher inference quality and with Act Order for even higher accuracy. | 
-| gptq-8bit-32g-actorder_True | 8 | 32 | Yes | 0.1 | [VMware Open Instruct](https://huggingface.co/datasets/VMware/open-instruct/viewer/) | 2048 | 3.28 GB | No | 8-bit, with group size 32g and Act Order for maximum inference quality. | 
-| gptq-4bit-64g-actorder_True | 4 | 64 | Yes | 0.1 | [VMware Open Instruct](https://huggingface.co/datasets/VMware/open-instruct/viewer/) | 2048 | 1.89 GB | No | 4-bit, with Act Order and group size 64g. Uses less VRAM than 32g, but with slightly lower accuracy. |
+| [main](https://huggingface.co/TheBloke/phi-2-GPTQ/tree/main) | 4 | 128 | Yes | 0.1 | [VMware Open Instruct](https://huggingface.co/datasets/VMware/open-instruct/viewer/) | 2048 | 1.84 GB | No | 4-bit, with Act Order and group size 128g. Uses even less VRAM than 64g, but with slightly lower accuracy. | 
+| [gptq-4bit-32g-actorder_True](https://huggingface.co/TheBloke/phi-2-GPTQ/tree/gptq-4bit-32g-actorder_True) | 4 | 32 | Yes | 0.1 | [VMware Open Instruct](https://huggingface.co/datasets/VMware/open-instruct/viewer/) | 2048 | 1.98 GB | No | 4-bit, with Act Order and group size 32g. Gives highest possible inference quality, with maximum VRAM usage. | 
+| [gptq-8bit--1g-actorder_True](https://huggingface.co/TheBloke/phi-2-GPTQ/tree/gptq-8bit--1g-actorder_True) | 8 | None | Yes | 0.1 | [VMware Open Instruct](https://huggingface.co/datasets/VMware/open-instruct/viewer/) | 2048 | 3.05 GB | No | 8-bit, with Act Order. No group size, to lower VRAM requirements. | 
+| [gptq-8bit-128g-actorder_True](https://huggingface.co/TheBloke/phi-2-GPTQ/tree/gptq-8bit-128g-actorder_True) | 8 | 128 | Yes | 0.1 | [VMware Open Instruct](https://huggingface.co/datasets/VMware/open-instruct/viewer/) | 2048 | 3.10 GB | No | 8-bit, with group size 128g for higher inference quality and with Act Order for even higher accuracy. | 
+| [gptq-8bit-32g-actorder_True](https://huggingface.co/TheBloke/phi-2-GPTQ/tree/gptq-8bit-32g-actorder_True) | 8 | 32 | Yes | 0.1 | [VMware Open Instruct](https://huggingface.co/datasets/VMware/open-instruct/viewer/) | 2048 | 3.28 GB | No | 8-bit, with group size 32g and Act Order for maximum inference quality. | 
+| [gptq-4bit-64g-actorder_True](https://huggingface.co/TheBloke/phi-2-GPTQ/tree/gptq-4bit-64g-actorder_True) | 4 | 64 | Yes | 0.1 | [VMware Open Instruct](https://huggingface.co/datasets/VMware/open-instruct/viewer/) | 2048 | 1.89 GB | No | 4-bit, with Act Order and group size 64g. Uses less VRAM than 32g, but with slightly lower accuracy. |
 
 <!-- README_GPTQ.md-provided-files end -->
 
@@ -193,8 +192,6 @@ Note that using Git with HF repos is strongly discouraged. It will be much slowe
 
 Please make sure you're using the latest version of [text-generation-webui](https://github.com/oobabooga/text-generation-webui).
 
-**NOTE** Will only work with `Loader: Transformers`, and requires `trust_remote_code=True`
-
 It is strongly recommended to use the text-generation-webui one-click-installers unless you're sure you know how to make a manual install.
 
 1. Click the **Model tab**.