Update README.md

README.md

@@ -1,3 +1,125 @@
 ---
 license: other
+inference: false
 ---
+
+# OpenAssistant LLaMA 30B SFT 7 GGML
+
+This in HF format repo of [OpenAssistant's LLaMA 30B SFT 7](https://huggingface.co/OpenAssistant/oasst-sft-7-llama-30b-xor).
+
+It is the result of merging the XORs from the above repo with the original Llama 30B weights, and then quantising to 4bit and 5bit GGML for CPU inference using [llama.cpp](https://github.com/ggerganov/llama.cpp).
+
+This is epoch 7 of OpenAssistant's training of their Llama 30B model.
+
+## Repositories available
+
+* [4bit GPTQ models for GPU inference](https://huggingface.co/TheBloke/OpenAssistant-SFT-7-Llama-30B-GPTQ).
+* [4bit and 5bit GGML models for CPU inference](https://huggingface.co/TheBloke/OpenAssistant-SFT-7-Llama-30B-GGML).
+* [Unquantised 16bit model in HF format](https://huggingface.co/TheBloke/OpenAssistant-SFT-7-Llama-30B-HF).
+
+## PROMPT TEMPLATE
+
+This model requires the following prompt template:
+
+```
+<|prompter|> prompt goes here
+<|assistant|>:
+```
+
+## Provided files
+| Name | Quant method | Bits | Size | RAM required | Use case |
+| ---- | ---- | ---- | ---- | ---- | ----- |
+`OpenAssistant-Llama30B-epoch7.ggml.q4_0.bin` | q4_0 | 4bit | 19GB | 21GB | Maximum compatibility |
+`OpenAssistant-Llama30B-epoch7.ggml.q4_2.bin` | q4_2 | 4bit | 19GB | 21GB | Best compromise between resources, speed and quality |
+`OpenAssistant-Llama30B-epoch7.ggml.q5_0.bin` | q5_0 | 5bit | 21GB | 23GB | Brand new 5bit method. Potentially higher quality than 4bit, at cost of slightly higher resources. |
+`OpenAssistant-Llama30B-epoch7.ggml.q5_1.bin` | q5_1 | 5bit | 23GB | 25GB | Brand new 5bit method. Slightly higher resource usage than q5_0.|
+
+* The q4_0 file provides lower quality, but maximal compatibility. It will work with past and future versions of llama.cpp
+* The q4_2 file offers the best combination of performance and quality. This format is still subject to change and there may be compatibility issues, see below.
+* The q5_0 file is using brand new 5bit method released 26th April. This is the 5bit equivalent of q4_0.
+* The q5_1 file is using brand new 5bit method released 26th April. This is the 5bit equivalent of q4_1.
+
+## q4_2 compatibility
+
+q4_2 is a relatively new 4bit quantisation method offering improved quality. However they are still under development and their formats are subject to change.
+
+In order to use these files you will need to use recent llama.cpp code. And it's possible that future updates to llama.cpp could require that these files are re-generated.
+
+If and when the q4_2 file no longer works with recent versions of llama.cpp I will endeavour to update it.
+
+If you want to ensure guaranteed compatibility with a wide range of llama.cpp versions, use the q4_0 file.
+
+## q5_0 and q5_1 compatibility
+
+These new methods were released to llama.cpp on 26th April. You will need to pull the latest llama.cpp code and rebuild to be able to use them.
+
+Don't expect any third-party UIs/tools to support them yet.
+
+## How to run in `llama.cpp`
+
+I use the following command line; adjust for your tastes and needs:
+
+```
+./main -t 18 -m OpenAssistant-Llama30B-epoch7.ggml.q4_2.bin --color -c 2048 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "<|prompter|>Write a very story about llamas <|assistant|>:"
+```
+
+Change `-t 18` to the number of physical CPU cores you have. For example if your system has 8 cores/16 threads, use `-t 8`.
+
+## How to run in `text-generation-webui`
+
+GGML models can be loaded into text-generation-webui by installing the llama.cpp module, then placing the ggml model file in a model folder as usual.
+
+Further instructions here: [text-generation-webui/docs/llama.cpp-models.md](https://github.com/oobabooga/text-generation-webui/blob/main/docs/llama.cpp-models.md).
+
+Note: at this time text-generation-webui will not support the new q5 quantisation methods.
+
+**Thireus** has written a [great guide on how to update it to the latest llama.cpp code](https://huggingface.co/TheBloke/wizardLM-7B-GGML/discussions/5) so that these files can be used in the UI.
+
+# Original model card
+
+```
+llama-30b-sft-7:
+  dtype: fp16
+  log_dir: "llama_log_30b"
+  learning_rate: 1e-5
+  model_name: /home/ubuntu/Open-Assistant/model/model_training/.saved/llama-30b-super-pretrain/checkpoint-3500
+  #model_name: OpenAssistant/llama-30b-super-pretrain
+  output_dir: llama_model_30b
+  deepspeed_config: configs/zero3_config_sft.json
+  weight_decay: 0.0
+  residual_dropout: 0.0
+  max_length: 2048
+  use_flash_attention: true
+  warmup_steps: 20
+  gradient_checkpointing: true
+  gradient_accumulation_steps: 12
+  per_device_train_batch_size: 2
+  per_device_eval_batch_size: 3
+  eval_steps: 101
+  save_steps: 485
+  num_train_epochs: 4
+  save_total_limit: 3
+  use_custom_sampler: true
+  sort_by_length: false
+  #save_strategy: steps
+  save_strategy: epoch
+  datasets:
+    - oasst_export:
+        lang: "bg,ca,cs,da,de,en,es,fr,hr,hu,it,nl,pl,pt,ro,ru,sl,sr,sv,uk"
+        input_file_path: 2023-04-12_oasst_release_ready_synth.jsonl.gz
+        val_split: 0.05
+    - vicuna:
+        val_split: 0.05
+        max_val_set: 800
+        fraction: 1.0
+    - dolly15k:
+        val_split: 0.05
+        max_val_set: 300
+    - grade_school_math_instructions:
+        val_split: 0.05
+    - code_alpaca:
+        val_split: 0.05
+        max_val_set: 250
+```
+
+- **OASST dataset paper:** https://arxiv.org/abs/2304.07327