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 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
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+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,211 @@
+---
+license: apache-2.0
+language:
+- en
+tags:
+- chat
+pipeline_tag: text-generation
+library_name: transformers
+---
+
+## AWQ Quantization Note
+My favorite model is Qwen2.5-72B-Instruct, but it responds a little dry sometimes, so I tried this model to see if it provided better response. Unfortunately, it doesn't perform as well for my primary RAG/tools use cases that require more stricter adherance to previous context.
+
+Qwen2.5-72B and derived models have an extra padding step required to quantize to AWQ in a way that supports tensor parallelism with vLLM and other services, so in the event that others find this model suitable for their needs, I'm uploading my AWQ 4-bit quant which first follows the paddings step at the bottom of [this page](https://qwen.readthedocs.io/en/latest/quantization/gptq.html)
+
+## MAIN MODEL CARD:
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/658a46cbfb9c2bdfae75b3a6/ZmOOkB2QwItLmoqmnxNWO.png)
+
+
+This is a series of models designed to replicate the prose quality of the Claude 3 models, specifically Sonnet and Opus.
+
+experimental because trained on top of instruct; but turned out amazing; hence code named magnum-alter, the original model that kickstarted the v4 family
+
+This model is fine-tuned on top of [Qwen2.5-72B-Instruct](https://huggingface.co/Qwen/Qwen2.5-72B-Instruct).
+
+## Prompting
+A typical input would look like this:
+
+```py
+<|im_start|>system
+system prompt<|im_end|>
+<|im_start|>user
+Hi there!<|im_end|>
+<|im_start|>assistant
+Nice to meet you!<|im_end|>
+<|im_start|>user
+Can I ask a question?<|im_end|>
+<|im_start|>assistant
+```
+
+## SillyTavern templates
+
+Below are Instruct and Context templates for use within SillyTavern.
+
+<details><summary>context template</summary>
+  
+```yaml
+{
+  "story_string": "<|im_start|>system\n{{#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}}{{trim}}<|im_end|>\n",
+  "example_separator": "",
+  "chat_start": "",
+  "use_stop_strings": false,
+  "allow_jailbreak": false,
+  "always_force_name2": true,
+  "trim_sentences": false,
+  "include_newline": false,
+  "single_line": false,
+  "name": "Magnum ChatML"
+}
+```
+
+</details><br>
+<details><summary>instruct template</summary>
+  
+```yaml
+{
+  "system_prompt": "Currently, your role is {{char}}, described in detail below. As {{char}}, continue the narrative exchange with {{user}}.\n\n<Guidelines>\n• Maintain the character persona but allow it to evolve with the story.\n• Be creative and proactive. Drive the story forward, introducing plotlines and events when relevant.\n• All types of outputs are encouraged; respond accordingly to the narrative.\n• Include dialogues, actions, and thoughts in each response.\n• Utilize all five senses to describe scenarios within {{char}}'s dialogue.\n• Use emotional symbols such as "!" and "~" in appropriate contexts.\n• Incorporate onomatopoeia when suitable.\n• Allow time for {{user}} to respond with their own input, respecting their agency.\n• Act as secondary characters and NPCs as needed, and remove them when appropriate.\n• When prompted for an Out of Character [OOC:] reply, answer neutrally and in plaintext, not as {{char}}.\n</Guidelines>\n\n<Forbidden>\n• Using excessive literary embellishments and purple prose unless dictated by {{char}}'s persona.\n• Writing for, speaking, thinking, acting, or replying as {{user}} in your response.\n• Repetitive and monotonous outputs.\n• Positivity bias in your replies.\n• Being overly extreme or NSFW when the narrative context is inappropriate.\n</Forbidden>\n\nFollow the instructions in <Guidelines></Guidelines>, avoiding the items listed in <Forbidden></Forbidden>.",
+  "input_sequence": "<|im_start|>user\n",
+  "output_sequence": "<|im_start|>assistant\n",
+  "last_output_sequence": "",
+  "system_sequence": "<|im_start|>system\n",
+  "stop_sequence": "<|im_end|>",
+  "wrap": false,
+  "macro": true,
+  "names": true,
+  "names_force_groups": true,
+  "activation_regex": "",
+  "system_sequence_prefix": "",
+  "system_sequence_suffix": "",
+  "first_output_sequence": "",
+  "skip_examples": false,
+  "output_suffix": "<|im_end|>\n",
+  "input_suffix": "<|im_end|>\n",
+  "system_suffix": "<|im_end|>\n",
+  "user_alignment_message": "",
+  "system_same_as_user": false,
+  "last_system_sequence": "",
+  "name": "Magnum ChatML"
+}
+```
+
+</details><br>
+
+## Axolotl config
+
+<details><summary>See axolotl config</summary>
+
+```yaml
+base_model: /workspace/data/models/Qwen2.5-72B-Instruct
+model_type: AutoModelForCausalLM
+tokenizer_type: AutoTokenizer
+
+plugins:
+  - axolotl.integrations.liger.LigerPlugin
+liger_rope: true
+liger_rms_norm: true
+liger_swiglu: true
+liger_fused_linear_cross_entropy: true
+
+load_in_8bit: false
+load_in_4bit: false
+strict: false
+
+datasets:
+  - path: anthracite-org/c2_logs_32k_llama3_qwen2_v1.2
+    type: sharegpt
+    conversation: chatml
+  - path: anthracite-org/kalo-opus-instruct-22k-no-refusal
+    type: sharegpt
+    conversation: chatml
+  - path: lodrick-the-lafted/kalo-opus-instruct-3k-filtered
+    type: sharegpt
+    conversation: chatml
+  - path: anthracite-org/nopm_claude_writing_fixed
+    type: sharegpt
+    conversation: chatml
+  - path: anthracite-org/kalo_opus_misc_240827
+    type: sharegpt
+    conversation: chatml
+  - path: anthracite-org/kalo_misc_part2
+    type: sharegpt
+    conversation: chatml
+#chat_template: chatml
+shuffle_merged_datasets: true
+#default_system_message: "You are an assistant that responds to the user."
+dataset_prepared_path: /workspace/data/magnum-72b-data
+val_set_size: 0.0
+output_dir: /workspace/data/72b-fft-out
+
+sequence_len: 32768
+sample_packing: true
+pad_to_sequence_len: true
+
+adapter:
+lora_model_dir:
+lora_r:
+lora_alpha:
+lora_dropout:
+lora_target_linear:
+lora_fan_in_fan_out:
+
+wandb_project: 72b-magnum-fft
+wandb_entity:
+wandb_watch:
+wandb_name: alter-attempt-01
+wandb_log_model:
+
+gradient_accumulation_steps: 2
+micro_batch_size: 1
+num_epochs: 2
+optimizer: adamw_bnb_8bit
+lr_scheduler: cosine
+learning_rate: 0.000004
+
+train_on_inputs: false
+group_by_length: false
+bf16: auto
+fp16:
+tf32: false
+
+gradient_checkpointing: true
+early_stopping_patience:
+resume_from_checkpoint:
+local_rank:
+logging_steps: 1
+xformers_attention:
+flash_attention: true
+
+warmup_steps: 40
+evals_per_epoch:
+eval_table_size:
+eval_max_new_tokens:
+saves_per_epoch: 2
+debug:
+deepspeed: deepspeed_configs/zero3_bf16.json
+weight_decay: 0.01
+fsdp:
+fsdp_config:
+special_tokens:
+```
+</details><br>
+
+## Credits
+We'd like to thank [DoctorShotgun](https://huggingface.co/Doctor-Shotgun) for sponsoring the compute for this train.
+We would also like to thank all members of Anthracite who made this finetune possible. 
+
+## Datasets
+- [anthracite-org/c2_logs_32k_llama3_qwen2_v1.2](https://huggingface.co/datasets/anthracite-org/c2_logs_32k_llama3_qwen2_v1.2)
+- [anthracite-org/kalo-opus-instruct-22k-no-refusal](https://huggingface.co/datasets/anthracite-org/kalo-opus-instruct-22k-no-refusal)
+- [lodrick-the-lafted/kalo-opus-instruct-3k-filtered](https://huggingface.co/datasets/lodrick-the-lafted/kalo-opus-instruct-3k-filtered)
+- [anthracite-org/nopm_claude_writing_fixed](https://huggingface.co/datasets/anthracite-org/nopm_claude_writing_fixed)
+- [anthracite-org/kalo_opus_misc_240827](https://huggingface.co/datasets/anthracite-org/kalo_opus_misc_240827)
+- [anthracite-org/kalo_misc_part2](https://huggingface.co/datasets/anthracite-org/kalo_misc_part2)
+
+## Training
+We used  8x mi300x GPUs graciously provided by [DoctorShotgun](https://huggingface.co/Doctor-Shotgun) for the full-parameter fine-tuning of the model.
+
+[<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)
+
+## Safety
+...

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config.json

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+  "architectures": [
+    "Qwen2ForCausalLM"
+  ],
+  "attention_dropout": 0.0,
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+  "max_window_layers": 80,
+  "model_type": "qwen2",
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+  "num_hidden_layers": 80,
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+  "quantization_config": {
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+    "quant_method": "awq",
+    "version": "gemm",
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+  "transformers_version": "4.45.2",
+  "use_cache": false,
+  "use_sliding_window": false,
+  "vocab_size": 152064
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+  ],
+  "bos_token": null,
+  "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0]['role'] == 'system' %}\n        {{- messages[0]['content'] }}\n    {%- else %}\n        {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}\n    {%- endif %}\n    {{- \"\\n\\n# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n    {%- if messages[0]['role'] == 'system' %}\n        {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n    {%- else %}\n        {{- '<|im_start|>system\\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n    {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n        {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {{- '<|im_start|>' + message.role }}\n        {%- if message.content %}\n            {{- '\\n' + message.content }}\n        {%- endif %}\n        {%- for tool_call in message.tool_calls %}\n            {%- if tool_call.function is defined %}\n                {%- set tool_call = tool_call.function %}\n            {%- endif %}\n            {{- '\\n<tool_call>\\n{\"name\": \"' }}\n            {{- tool_call.name }}\n            {{- '\", \"arguments\": ' }}\n            {{- tool_call.arguments | tojson }}\n            {{- '}\\n</tool_call>' }}\n        {%- endfor %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- message.content }}\n        {{- '\\n</tool_response>' }}\n        {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "model_max_length": 131072,
+  "pad_token": "<|endoftext|>",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}