Create README.md

README.md

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+---
+license: apache-2.0
+language:
+  - en
+tags:
+  - sft
+pipeline_tag: text-generation
+widget:
+  - text: <|prompter|>What is a meme, and what's the history behind this word?<|endoftext|><|assistant|>
+  - text: <|prompter|>What's the Earth total population<|endoftext|><|assistant|>
+  - text: <|prompter|>Write a story about future of AI development<|endoftext|><|assistant|>
+---
+
+# Open-Assistant StableLM-7B SFT-7 Model
+
+
+This is the 4th iteration English supervised-fine-tuning (SFT) model of 
+the [Open-Assistant](https://github.com/LAION-AI/Open-Assistant) project. 
+It is based on a Pythia 12B that was fine-tuned on human demonstrations 
+of assistant conversations collected through the 
+[https://open-assistant.io/](https://open-assistant.io/) human feedback web 
+app before March 25, 2023. 
+
+## Model Details
+
+- **Developed by:** [Open-Assistant Contributors](https://open-assistant.io/)
+- **Model type:** Transformer-based Language Model
+- **Language:** English
+- **Finetuned from:** [stabilityai/stablelm-base-alpha-7b](https://huggingface.co/stabilityai/stablelm-base-alpha-7b)
+- **Code:** [Open-Assistant/model/model_training](https://github.com/LAION-AI/Open-Assistant/tree/main/model/model_training)
+- **Demo:** TODO
+- **License:** Creative Commons license ([CC BY-SA-4.0](https://creativecommons.org/licenses/by-sa/4.0/))
+- **Contact:** [Open-Assistant Discord](https://ykilcher.com/open-assistant-discord)
+
+## Prompting
+
+Two special tokens are used to mark the beginning of user and assistant turns:
+`<|prompter|>` and `<|assistant|>`. Each turn ends with a `<|endoftext|>` token.
+
+Input prompt example:
+```
+<|prompter|>What is a meme, and what's the history behind this word?<|endoftext|><|assistant|>
+```
+The input ends with the `<|assistant|>` token to signal that the model should 
+start generating the assistant reply.
+
+
+## Dev Details
+
+- wandb: https://wandb.ai/open-assistant/supervised-finetuning/runs/08dfhyuc
+- base model: [stabilityai/stablelm-base-alpha-7b](https://huggingface.co/stabilityai/stablelm-base-alpha-7b)
+- checkpoint: 3 epochs (12000 steps)
+
+command: `deepspeed trainer_sft.py --configs defaults reference-data reference-pythia-12b --cache_dir /home/ubuntu/data_cache --output_dir .saved/oasst-sft-3-pythia-12b-reference_2kpre --num_train_epochs 8 --residual_dropout 0.2 --deepspeed --use_flash_attention true --model_name andreaskoepf/pythia-12b-pre-2000`
+
+data:
+```
+oasst-mix:
+  save_strategy: epoch
+  sort_by_length: false
+  use_custom_sampler: false
+  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
+    - 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
+```
+
+
+stablelm:
+```
+stablelm-7b:
+  dtype: fp16
+  log_dir: stablelm_log_7b
+  model_name: stabilityai/stablelm-base-alpha-7b
+  output_dir: stablelm_7b
+  max_length: 4096
+  warmup_steps: 100
+  gradient_checkpointing: true
+  gradient_accumulation_steps: 2
+  per_device_train_batch_size: 4
+  per_device_eval_batch_size: 4
+  eval_steps: 100
+  save_steps: 500
+  num_train_epochs: 4
+  save_total_limit: 4
+  use_flash_attention: true
+```
+
+zero config:
+```
+{
+  "fp16": {
+    "enabled": "auto",
+    "loss_scale": 0,
+    "loss_scale_window": 1000,
+    "initial_scale_power": 16,
+    "hysteresis": 2,
+    "min_loss_scale": 1
+  },
+  "bf16": {
+    "enabled": "auto"
+  },
+  "optimizer": {
+    "type": "AdamW",
+    "params": {
+      "lr": "auto",
+      "betas": "auto",
+      "eps": "auto",
+      "weight_decay": "auto"
+    }
+  },
+  "scheduler": {
+    "type": "WarmupDecayLR",
+    "params": {
+      "warmup_min_lr": "auto",
+      "warmup_max_lr": "auto",
+      "warmup_num_steps": "auto",
+      "total_num_steps": "auto"
+    }
+  },
+  "zero_optimization": {
+    "stage": 2,
+    "allgather_partitions": true,
+    "allgather_bucket_size": 1e9,
+    "overlap_comm": false,
+    "reduce_scatter": true,
+    "reduce_bucket_size": 1e9,
+    "contiguous_gradients": true
+  },
+  "gradient_accumulation_steps": "auto",
+  "gradient_clipping": "auto",
+  "steps_per_print": 2000,
+  "train_batch_size": "auto",
+  "train_micro_batch_size_per_gpu": "auto",
+  "wall_clock_breakdown": false
+}
+```