Upload model weights (#1)
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- Magnum-Mistral-Context.json +12 -0
- Magnum-Mistral-Instruct.json +24 -0
- README.md +60 -0
- config.json +38 -0
- generation_config.json +7 -0
- huggingface-metadata.txt +56 -0
- model.safetensors.index.json +802 -0
- output-00001-of-00013.safetensors +3 -0
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- output-00013-of-00013.safetensors +3 -0
- special_tokens_map.json +24 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +0 -0
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{
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"story_string": "[INST] {{#if system}} {{system}}\n{{/if}}{{#if wiBefore}}{{wiBefore}}\n{{/if}}{{#if description}}{{description}}\n{{/if}}{{#if personality}}{{char}}'s personality: {{personality}}\n{{/if}}{{#if scenario}}Scenario: {{scenario}}\n{{/if}}{{#if wiAfter}}{{wiAfter}}\n{{/if}}{{#if persona}}{{persona}}\n{{/if}}\nLet's get started. Please respond based on the information and instructions provided above.[/INST] ",
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"example_separator": "",
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"chat_start": "",
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"use_stop_strings": false,
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"allow_jailbreak": false,
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"always_force_name2": true,
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"trim_sentences": false,
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"include_newline": false,
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"single_line": false,
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"name": "Mistral"
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}
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{
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"system_prompt": "Write {{char}}'s next reply in this fictional roleplay with {{user}}.",
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"input_sequence": "[INST] ",
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"output_sequence": "",
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"last_output_sequence": "",
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"system_sequence": "",
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"stop_sequence": "</s>",
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"wrap": false,
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"macro": true,
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"names": true,
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"names_force_groups": true,
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"activation_regex": "",
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"system_sequence_prefix": "",
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"system_sequence_suffix": "",
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"first_output_sequence": "",
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"skip_examples": false,
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"output_suffix": "</s>",
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"input_suffix": "[/INST] ",
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"system_suffix": "",
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"user_alignment_message": "",
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"system_same_as_user": true,
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"last_system_sequence": "",
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"name": "Mistral"
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}
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---
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license: other
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license_name: mrl
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license_link: https://mistral.ai/licenses/MRL-0.1.md
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language:
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- en
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- fr
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- de
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- es
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- it
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- pt
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- ru
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- zh
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- ja
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pipeline_tag: text-generation
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tags:
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- chat
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---
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/6491e00e057b0928b3e07b75/hkPzhL-xYPeGGKCyAf3Qd.png)
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This is the sixth in a series of models designed to replicate the prose quality of the Claude 3 models, specifically Sonnet and Opus. This model is fine-tuned on top of [Mistral-Large-Instruct-2407](https://huggingface.co/mistralai/Mistral-Large-Instruct-2407).
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## Prompting
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Model has been Instruct tuned with the Mistral formatting. A typical input would look like this:
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```py
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<s>[INST] SYSTEM MESSAGE\nUSER MESSAGE[/INST] ASSISTANT MESSAGE</s>[INST] USER MESSAGE[/INST]
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```
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We also provide SillyTavern presets for [Context](https://huggingface.co/anthracite-org/Magnum-123b-v1/resolve/main/Magnum-Mistral-Context.json) and [Instruct](https://huggingface.co/anthracite-org/Magnum-123b-v1/raw/main/Magnum-Mistral-Instruct.json) respectively.
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The Mistral preset included in SillyTavern seems to be misconfigured by default, so we recommend using these as a replacement.
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## Credits
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- [anthracite-org/Stheno-Data-Filtered](https://huggingface.co/datasets/anthracite-org/Stheno-Data-Filtered)
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- [anthracite-org/kalo-opus-instruct-22k-no-refusal](https://huggingface.co/datasets/anthracite-org/kalo-opus-instruct-22k-no-refusal)
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- [anthracite-org/nopm_claude_writing_fixed](https://huggingface.co/datasets/anthracite-org/nopm_claude_writing_fixed)
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This model has been a team effort, and the credits goes to all members of Anthracite.
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## Training
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The training was done for 1.5 epochs. We used 8x [AMD Instinct™ MI300X Accelerators](https://www.amd.com/en/products/accelerators/instinct/mi300/mi300x.html) for the full-parameter fine-tuning of the model.
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In addition to this, we noticed that Mistral Large models seemed much more sensitive to learning rate adjustments than other models:
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/6491e00e057b0928b3e07b75/xCK3ISKF6pWcMyO7MEzTA.png)
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We hypothesize this is primarily due to the particularly narrow and low variance weight distributions typical of Mistral derived models regardless of their scale.
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In the end, due to the costs that would be involved in training another full 2 epochs run ($600) on an even lower rate, we settled on our third attempt: 2e-6 with an effective batch size of 64. We chose to publish the 1.5 epoch run after manually testing and comparing it.
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/6491e00e057b0928b3e07b75/d9_cBy-DuWrdnoVBbAvRV.png)
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Also, we notice a correlation between the significance of the 2nd epoch loss drop and the strength of the learning rate, implying 4e-6 leads to more catastrophic forgetting.
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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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## Safety
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...
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{
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"_name_or_path": "anthracite-org/magnum-v2-123b",
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"architectures": [
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"MistralForCausalLM"
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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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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 12288,
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"initializer_range": 0.02,
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"intermediate_size": 28672,
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"max_position_embeddings": 131072,
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"model_type": "mistral",
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"num_attention_heads": 96,
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"num_hidden_layers": 88,
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"num_key_value_heads": 8,
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"rms_norm_eps": 1e-05,
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"rope_theta": 1000000.0,
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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": "4.43.4",
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"use_cache": false,
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"vocab_size": 32768,
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"quantization_config": {
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"quant_method": "exl2",
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"version": "0.1.8",
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"bits": 7.0,
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"head_bits": 8,
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"calibration": {
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"rows": 115,
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"length": 2048,
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"dataset": "(default)"
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}
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}
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}
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{
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"_from_model_config": true,
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"bos_token_id": 1,
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"do_sample": true,
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"eos_token_id": 2,
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"transformers_version": "4.43.4"
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}
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url: https://huggingface.co/anthracite-org/magnum-v2-123b
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branch: main
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download date: 2024-08-20 20:38:17
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