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LoneStriker
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MixtralRPChat-ZLoss-3.0bpw-h6-exl2

Text Generation
Transformers
Safetensors
English
mixtral
conversational
text-generation-inference
Inference Endpoints
Model card Files Community
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  1. README.md +25 -0
  2. axolotl_config.yml +91 -0
  3. config.json +29 -0
  4. generation_config.json +6 -0
  5. model.safetensors.index.json +1002 -0
  6. output-00001-of-00003.safetensors +3 -0
  7. output-00002-of-00003.safetensors +3 -0
  8. output-00003-of-00003.safetensors +3 -0
  9. special_tokens_map.json +30 -0
  10. tokenizer.json +0 -0
  11. tokenizer.model +3 -0
  12. tokenizer_config.json +43 -0
  13. webui-prompt-template.yml +24 -0
README.md ADDED
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+ ---
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+ license: cc-by-nc-4.0
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+ datasets:
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+ - Open-Orca/SlimOrca
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+ - lemonilia/LimaRP
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+ - chargoddard/rpguild
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+ - chargoddard/summarize_from_feedback_alpaca
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+ - HuggingFaceH4/no_robots
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+ - chargoddard/coedit-reworded
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+ language:
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+ - en
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+ tags:
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+ - mixtral
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+ base_model: mistralai/Mixtral-8x7B-v0.1
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+ ---
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+
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+ [<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
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+
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+ QLoRA tuned from [mistralai/Mixtral-8x7B-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1).
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+
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+ My main reason for training this model was to investigate using an altered router balancing loss combined with the z-loss introduced in [ST-MoE: Designing Stable and Transferable Sparse Expert Models](https://arxiv.org/abs/2202.08906). The result is pretty decent, I think! It does a good job of respecting character information in system prompts and performed adequately on a few simple coding tasks.
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+
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+ To train this I used a custom branch of Transformers that adds z-loss and reimplements the router balancing loss based on the version in [MegaBlocks](https://github.com/stanford-futuredata/megablocks). The config used with my custom hacked-up branch of axolotl is available [here](https://huggingface.co/chargoddard/MixtralRPChat-ZLoss/blob/main/axolotl_config.yml).
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+
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+ Uses my favorite non-ChatML token-economic chat prompt format. Messages should be prefixed with `" ***System:"`, `" ***Query:"`, or `" ***Response:"` for system, user, and model messages respectively. No newlines are necessary but the space before the triple asterisk is mandatory.
axolotl_config.yml ADDED
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+ base_model: mistralai/Mixtral-8x7B-v0.1
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+ model_type: AutoModelForCausalLM
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+ tokenizer_type: AutoTokenizer
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+
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+ model_config:
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+ output_router_logits: true
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+ router_aux_loss_coef: 0.02
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+ router_z_loss_coef: 0.001
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+
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+ load_in_8bit: false
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+ load_in_4bit: true
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+ strict: false
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+
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+ datasets:
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+ - path: /workspace/data/rpguild-grammar-filtered.jsonl
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+ type: rp_forum
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+ shards: 4
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+ - path: /workspace/limaerp-8192.jsonl
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+ type: rp_forum
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+ repeats: 2
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+ - path: /workspace/data/no-robots-rp.jsonl
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+ type: pippa
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+ - path: Open-Orca/SlimOrca
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+ type: sharegpt
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+ shards: 15
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+ - path: chargoddard/summarize_from_feedback_alpaca
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+ type: alpaca
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+ shards: 14
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+ - path: chargoddard/coedit-reworded
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+ type: alpaca
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+ shards: 14
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+ prompt_format: economic_rp
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+ dataset_prepared_path: last_run_prepared
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+ val_set_size: 0.04
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+ output_dir: ./mixtral-lora
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+ save_safetensors: true
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+
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+ adapter: qlora
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+ lora_model_dir:
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+
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+ sequence_len: 8192
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+ sample_packing: true
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+ pad_to_sequence_len: true
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+
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+ lora_r: 128
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+ lora_alpha: 256
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+ lora_dropout: 0.05
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+ lora_target_linear: true
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+ lora_fan_in_fan_out:
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+ # lora_target_modules:
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+
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+ wandb_project: mixtral-lora
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+ wandb_entity:
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+ wandb_watch:
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+ wandb_run_id:
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+ wandb_log_model:
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+
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+ gradient_accumulation_steps: 16
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+ micro_batch_size: 2
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+ eval_batch_size: 2
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+ num_epochs: 1
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+ optimizer: adamw_bnb_8bit
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+ lr_scheduler: cosine
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+ learning_rate: 0.00025
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+
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+ train_on_inputs: false
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+ group_by_length: false
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+ bf16: true
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+ fp16: false
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+ tf32: false
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+
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+ gradient_checkpointing: true
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+ early_stopping_patience:
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+ resume_from_checkpoint:
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+ auto_resume_from_checkpoints: true
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+ local_rank:
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+ logging_steps: 1
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+ xformers_attention:
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+ flash_attention: true
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+ save_total_limit: 2
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+
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+ warmup_steps: 10
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+ eval_steps: 0.05
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+ save_steps: 0.05
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+ eval_table_size:
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+ eval_table_max_new_tokens: 128
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+ weight_decay: 0.0
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+ special_tokens:
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+ bos_token: "<s>"
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+ eos_token: "</s>"
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+ unk_token: "<unk>"
config.json ADDED
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+ {
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+ "architectures": [
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+ "MixtralForCausalLM"
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+ ],
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+ "attention_dropout": 0.0,
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+ "bos_token_id": 1,
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+ "eos_token_id": 2,
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+ "hidden_act": "silu",
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+ "hidden_size": 4096,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 14336,
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+ "max_position_embeddings": 32768,
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+ "model_type": "mixtral",
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+ "num_attention_heads": 32,
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+ "num_experts_per_tok": 2,
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+ "num_hidden_layers": 32,
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+ "num_key_value_heads": 8,
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+ "num_local_experts": 8,
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+ "output_router_logits": false,
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+ "rms_norm_eps": 1e-05,
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+ "rope_theta": 1000000.0,
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+ "router_aux_loss_coef": 0.02,
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+ "sliding_window": null,
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "bfloat16",
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+ "transformers_version": "4.36.0.dev0",
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+ "use_cache": false,
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+ "vocab_size": 32000
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+ }
generation_config.json ADDED
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+ {
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+ "_from_model_config": true,
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+ "bos_token_id": 1,
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+ "eos_token_id": 2,
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+ "transformers_version": "4.36.0.dev0"
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+ }
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