Update README.md

README.md

@@ -12,6 +12,138 @@ tags:
 This model was converted to GGUF format from [`FourOhFour/Tulu-3.69-DPO-8B`](https://huggingface.co/FourOhFour/Tulu-3.69-DPO-8B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
 Refer to the [original model card](https://huggingface.co/FourOhFour/Tulu-3.69-DPO-8B) for more details on the model.
 
+---
+Model details:
+-
+This is a DPO applied over Tulu-3.69-8B. This model is designed to 
+roleplay and converse like a human chat partner. This model follows 
+instructions well and excels at playing characters in a realistic and 
+entertaining manner.
+
+
+For ease of use, try the Llama 3 instruct format. You may need to set a custom stop string for <|end_of_text|>
+
+
+For optimal performance I have found that a modified Tulu 3 instruct format is quite effective:
+
+
+<|system|>
+
+
+This is an instruction.
+
+
+<|end_of_text|>
+
+
+<|user|>
+
+
+This is the user input.
+
+
+<|assistant|>
+
+
+This is model output.
+
+
+<|end_of_text|>
+
+
+Further, if you want your bot to have a sense of time, you can set the last output prefix as such:
+
+
+<|system|>
+
+
+{{time}} {{weekday}} {{date}}
+
+
+<|end_of_text|>
+
+
+<|assistant|>
+
+
+Note: these macros may differ in your chosen inferencing frontend. Please correct accordingly.
+
+
+base_model: jeiku/Tulu-3.69-8B
+model_type: AutoModelForCausalLM
+tokenizer_type: AutoTokenizer
+
+load_in_8bit: false
+load_in_4bit: false
+strict: false
+
+hub_model_id: jeiku/tuludpo
+hub_strategy: "all_checkpoints"
+push_dataset_to_hub:
+hf_use_auth_token: true
+
+chat_template: llama3
+rl: dpo
+datasets:
+  - path: antiven0m/physical-reasoning-dpo
+    type: llama3.prompt_pairs
+  - path: nbeerbower/Purpura-DPO
+    type: llama3.prompt_pairs
+  - path: FourOhFour/Human_DPO_Emojis_Removed
+    type: llama3.prompt_pairs
+
+shuffle_merged_datasets: true
+val_set_size: 0.005
+output_dir: ./outputs/out
+
+sequence_len: 8192
+sample_packing: false
+eval_sample_packing: false
+pad_to_sequence_len: false
+
+wandb_project: evil
+wandb_entity:
+wandb_watch:
+wandb_name: evil
+wandb_log_model:
+
+gradient_accumulation_steps: 16
+micro_batch_size: 2
+num_epochs: 2
+optimizer: adamw_bnb_8bit
+lr_scheduler: cosine
+learning_rate: 0.000005
+weight_decay: 0.05
+
+train_on_inputs: false
+group_by_length: false
+bf16: auto
+fp16:
+tf32: true
+
+gradient_checkpointing: true
+early_stopping_patience:
+resume_from_checkpoint: 
+local_rank:
+logging_steps: 1
+xformers_attention:
+flash_attention: true
+
+warmup_steps: 10
+evals_per_epoch: 2
+eval_table_size:
+eval_max_new_tokens: 
+saves_per_epoch: 1
+
+debug:
+deepspeed:
+fsdp:
+fsdp_config:
+
+special_tokens:
+  pad_token: <|finetune_right_pad_id|>
+
+---
 ## Use with llama.cpp
 Install llama.cpp through brew (works on Mac and Linux)