Update README.md

README.md

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 ---
+inference: false
 license: llama2
+model_creator: WizardLM
+model_link: https://huggingface.co/WizardLM/WizardLM-70B-V1.0
+model_name: WizardLM 70B V1.0
+model_type: llama
+quantized_by: Thireus
 ---
+
+# WizardLM 70B V1.0 - EXL2
+- Model creator: [WizardLM](https://huggingface.co/WizardLM)
+- Original model: [WizardLM 70B V1.0](https://huggingface.co/WizardLM/WizardLM-70B-V1.0)
+- Quantized model: [WizardLM 70B V1.0-HF](https://huggingface.co/simsim314/WizardLM-70B-V1.0-HF) - float16 of WizardLM 70B V1.0
+
+| Branch | BITS (-b) | HEAD_BITS (-hb) | MEASUREMENT_LENGTH (-ml) | LENGTH (-l) | CAL_DATASET (-c) | Size | ExLlama | Max Context Length | Desc |
+| ------ | ---- | -- | --------- | ------ | ------------ | ------- | ---- | ------- | ---- |
+| [main](https://huggingface.co/Thireus/WizardLM-70B-V1.0-HF-4.0bpw-h6-exl2/tree/main) | 4.0 | 6 | 2048 | 2048 | [0000.parquet - wikitext-2-raw-v1](https://huggingface.co/datasets/wikitext/tree/refs%2Fconvert%2Fparquet/wikitext-2-raw-v1/train) | 33GB | [V2](https://github.com/turboderp/exllamav2) | 4096 | Equivalent, in theory, to QPTQ 4-bit. | 
+
+## Description
+
+This repository contains EXL2 model files for [WizardLM's WizardLM 70B V1.0](https://huggingface.co/WizardLM/WizardLM-70B-V1.0).
+
+EXL2 is the new format used by ExLlamaV2 - https://github.com/turboderp/exllamav2. EXL2 is based on the same optimization method as GPTQ. The format allows for mixing quantization
+levels within a model to achieve any average bitrate between 2 and 8 bits per weight.
+
+## Prompt template (official): Vicuna
+
+```
+A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: {prompt} ASSISTANT:
+
+```
+
+## Prompt template (Thireus' own suggestion):
+
+```
+A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions.
+USER:
+{prompt}
+ASSISTANT:
+
+```
+
+## Quantization process
+
+Original Model --> Float16 Model --> Safetensor Model --> EXL2 Model
+
+Example:
+[WizardLM 70B V1.0](https://huggingface.co/WizardLM/WizardLM-70B-V1.0) --> [WizardLM 70B V1.0-HF](https://huggingface.co/simsim314/WizardLM-70B-V1.0-HF) --> Safetensor --> EXL2
+
+Use any one of the following scripts to convert your float16 pytorch_model bin files to safetensors:
+- https://github.com/turboderp/exllamav2/blob/master/util/convert_safetensors.py
+- https://huggingface.co/Panchovix/airoboros-l2-70b-gpt4-1.4.1-safetensors/blob/main/bin2safetensors/convert.py
+- https://gist.github.com/epicfilemcnulty/1f55fd96b08f8d4d6693293e37b4c55e
+- https://github.com/oobabooga/text-generation-webui/blob/main/convert-to-safetensors.py
+
+Example to convert WizardLM-70B-V1.0-HF_float16_safetensored to EXL2 4.0 bpw with 6-bit head:
+```
+mkdir -p ~/EXL2/WizardLM-70B-V1.0-HF_4bit # Create the output directory
+python convert.py -i ~/safetensor/WizardLM-70B-V1.0-HF_float16_safetensored -o ~/EXL2/WizardLM-70B-V1.0-HF_4bit -c ~/EXL2/0000.parquet -b 4.0 -hb 6
+```