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README.md

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+---
+duplicated_from: localmodels/LLM
+---
+# OpenAssistant SFT 7 LLaMA 30B ggml
+
+From: https://huggingface.co/OpenAssistant/oasst-sft-7-llama-30b-xor
+
+---
+
+### Original llama.cpp quant methods: `q4_0, q4_1, q5_0, q5_1, q8_0`
+
+Quantized using an older version of llama.cpp and compatible with llama.cpp from May 19, commit 2d5db48.
+
+### k-quant methods: `q2_K, q3_K_S, q3_K_M, q3_K_L, q4_K_S, q4_K_M, q5_K_S, q6_K`
+
+Quantization methods compatible with latest llama.cpp from June 6, commit 2d43387.
+
+---
+
+## Provided files
+| Name | Quant method | Bits | Size | Max RAM required | Use case |
+| ---- | ---- | ---- | ---- | ---- | ----- |
+| OpenAssistant-SFT-7-Llama-30B.ggmlv3.q2_K.bin | q2_K | 2 | 13.60 GB | 16.10 GB | New k-quant method. Uses GGML_TYPE_Q4_K for the attention.vw and feed_forward.w2 tensors, GGML_TYPE_Q2_K for the other tensors. |
+| OpenAssistant-SFT-7-Llama-30B.ggmlv3.q3_K_L.bin | q3_K_L | 3 | 17.20 GB | 19.70 GB | New k-quant method. Uses GGML_TYPE_Q5_K for the attention.wv, attention.wo, and feed_forward.w2 tensors, else GGML_TYPE_Q3_K |
+| OpenAssistant-SFT-7-Llama-30B.ggmlv3.q3_K_M.bin | q3_K_M | 3 | 15.64 GB | 18.14 GB | New k-quant method. Uses GGML_TYPE_Q4_K for the attention.wv, attention.wo, and feed_forward.w2 tensors, else GGML_TYPE_Q3_K |
+| OpenAssistant-SFT-7-Llama-30B.ggmlv3.q3_K_S.bin | q3_K_S | 3 | 13.98 GB | 16.48 GB | New k-quant method. Uses GGML_TYPE_Q3_K for all tensors |
+| OpenAssistant-SFT-7-Llama-30B.ggmlv3.q4_0.bin | q4_0 | 4 | 18.30 GB | 20.80 GB | Original llama.cpp quant method, 4-bit. |
+| OpenAssistant-SFT-7-Llama-30B.ggmlv3.q4_K_M.bin | q4_K_M | 4 | 19.57 GB | 22.07 GB | New k-quant method. Uses GGML_TYPE_Q6_K for half of the attention.wv and feed_forward.w2 tensors, else GGML_TYPE_Q4_K |
+| OpenAssistant-SFT-7-Llama-30B.ggmlv3.q4_K_S.bin | q4_K_S | 4 | 18.30 GB | 20.80 GB | New k-quant method. Uses GGML_TYPE_Q4_K for all tensors |
+| OpenAssistant-SFT-7-Llama-30B.ggmlv3.q5_0.bin | q5_0 | 5 | 22.37 GB | 24.87 GB | Original llama.cpp quant method, 5-bit. Higher accuracy, higher resource usage and slower inference. |
+| OpenAssistant-SFT-7-Llama-30B.ggmlv3.q5_1.bin | q5_1 | 5 | 24.40 GB | 26.90 GB | Original llama.cpp quant method, 5-bit. Even higher accuracy, resource usage and slower inference. |
+| OpenAssistant-SFT-7-Llama-30B.ggmlv3.q5_K_M.bin | q5_K_M | 5 | 23.02 GB | 25.52 GB | New k-quant method. Uses GGML_TYPE_Q6_K for half of the attention.wv and feed_forward.w2 tensors, else GGML_TYPE_Q5_K |
+| OpenAssistant-SFT-7-Llama-30B.ggmlv3.q5_K_S.bin | q5_K_S | 5 | 22.37 GB | 24.87 GB | New k-quant method. Uses GGML_TYPE_Q5_K for all tensors |
+| OpenAssistant-SFT-7-Llama-30B.ggmlv3.q6_K.bin | q6_K | 6 | 26.69 GB | 29.19 GB | New k-quant method. Uses GGML_TYPE_Q8_K - 6-bit quantization - for all tensors |
+
+---
+
+# OpenAssistant LLaMA 30B SFT 7
+
+### Configuration
+
+```
+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