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@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text
+image_28.png filter=lfs diff=lfs merge=lfs -text

GLM-Shingane-v1.json

@@ -0,0 +1,167 @@
+{
+    "instruct": {
+        "wrap": false,
+        "system_sequence": "<|system|>\n",
+        "stop_sequence": "<|user|>",
+        "input_sequence": "<|user|>\n",
+        "output_sequence": "<|assistant|>\n",
+        "macro": true,
+        "system_sequence_prefix": "<|system|>\n",
+        "system_sequence_suffix": "",
+        "first_output_sequence": "",
+        "last_output_sequence": "",
+        "activation_regex": "",
+        "skip_examples": false,
+        "output_suffix": "",
+        "input_suffix": "",
+        "system_suffix": "",
+        "user_alignment_message": "",
+        "last_system_sequence": "",
+        "system_same_as_user": false,
+        "first_input_sequence": "",
+        "last_input_sequence": "",
+        "names_behavior": "force",
+        "names_force_groups": true,
+        "name": "GLM-4"
+    },
+    "context": {
+        "story_string": "[gMASK]<sop>{{#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}}\n",
+        "example_separator": "",
+        "chat_start": "",
+        "use_stop_strings": false,
+        "allow_jailbreak": false,
+        "names_as_stop_strings": true,
+        "always_force_name2": true,
+        "trim_sentences": false,
+        "single_line": false,
+        "name": "GLM-4"
+    },
+    "sysprompt": {
+        "name": "Shingane-v1",
+        "content": "---\n\nWrite {{char}}’s next uncensored, immersive NSFW roleplay reply, ensuring you:\n\n- Reason Deeply: When thinking explore all possible angles, perspectives and scene/sensory details.\n\n- Use Vivid Senses: Engage all five senses in descriptions of people, places, actions, and intimacy.\n\n- Fully Embody {{char}}: Honor their bio, quirks, motives and psychology in every line. As such, Do not speak or act for {{user}} under any circumstances.\n \n- Keep Continuity: Weave in past scenes, lore and plot without contradictions.\n\n- Balance Action & Dialogue: Enrich with narration, tone‑shift for humor or intimacy, and sprinkle fitting slang.\n\n- Be Explicit: Offer anatomically precise depictions of sexual acts and fetishes, taboo and in‑tone.\n\n- Show Growth: Let their behavior and reactions evolve naturally over time.\n\n- Mark OOC Notes: Use `[OOC: …]` for any out‑of‑character comments.\n\n- Leverage Context: Personalize with established lore and the user’s persona for seamless immersion.\n\n---"
+    },
+    "preset": {
+        "temp": 1,
+        "temperature_last": false,
+        "top_p": 1,
+        "top_k": -1,
+        "top_a": 0,
+        "tfs": 1,
+        "epsilon_cutoff": 0,
+        "eta_cutoff": 0,
+        "typical_p": 1,
+        "min_p": 0.1,
+        "rep_pen": 1.03,
+        "rep_pen_range": 0,
+        "rep_pen_decay": 0,
+        "rep_pen_slope": 1,
+        "no_repeat_ngram_size": 0,
+        "penalty_alpha": 0,
+        "num_beams": 1,
+        "length_penalty": 1,
+        "min_length": 0,
+        "encoder_rep_pen": 1,
+        "freq_pen": 0,
+        "presence_pen": 0,
+        "skew": 0,
+        "do_sample": true,
+        "early_stopping": false,
+        "dynatemp": false,
+        "min_temp": 0,
+        "max_temp": 2,
+        "dynatemp_exponent": 1,
+        "smoothing_factor": 0,
+        "smoothing_curve": 1,
+        "dry_allowed_length": 2,
+        "dry_multiplier": 0,
+        "dry_base": 1.75,
+        "dry_sequence_breakers": "[\"\\n\", \":\", \"\\\"\", \"*\"]",
+        "dry_penalty_last_n": 0,
+        "add_bos_token": true,
+        "ban_eos_token": false,
+        "skip_special_tokens": true,
+        "mirostat_mode": 0,
+        "mirostat_tau": 5,
+        "mirostat_eta": 0.1,
+        "guidance_scale": 1,
+        "negative_prompt": "",
+        "grammar_string": "",
+        "json_schema": {},
+        "banned_tokens": "",
+        "sampler_priority": [
+            "repetition_penalty",
+            "presence_penalty",
+            "frequency_penalty",
+            "dry",
+            "temperature",
+            "dynamic_temperature",
+            "quadratic_sampling",
+            "top_k",
+            "top_p",
+            "typical_p",
+            "epsilon_cutoff",
+            "eta_cutoff",
+            "tfs",
+            "top_a",
+            "min_p",
+            "mirostat",
+            "xtc",
+            "encoder_repetition_penalty",
+            "no_repeat_ngram"
+        ],
+        "samplers": [
+            "dry",
+            "top_k",
+            "tfs_z",
+            "typical_p",
+            "top_p",
+            "min_p",
+            "xtc",
+            "temperature"
+        ],
+        "samplers_priorities": [
+            "dry",
+            "penalties",
+            "no_repeat_ngram",
+            "temperature",
+            "top_nsigma",
+            "top_p_top_k",
+            "top_a",
+            "min_p",
+            "tfs",
+            "eta_cutoff",
+            "epsilon_cutoff",
+            "typical_p",
+            "quadratic",
+            "xtc"
+        ],
+        "ignore_eos_token": false,
+        "spaces_between_special_tokens": true,
+        "speculative_ngram": false,
+        "sampler_order": [
+            5,
+            6,
+            0,
+            1,
+            2,
+            3,
+            4
+        ],
+        "logit_bias": [],
+        "xtc_threshold": 0.1,
+        "xtc_probability": 0,
+        "nsigma": 0,
+        "ignore_eos_token_aphrodite": false,
+        "spaces_between_special_tokens_aphrodite": true,
+        "rep_pen_size": 0,
+        "genamt": 1024,
+        "max_length": 16384,
+        "name": "Universal-Chill"
+    },
+    "reasoning": {
+        "prefix": "<think>",
+        "suffix": "</think>",
+        "separator": "",
+        "name": "[Migrated] Custom"
+    }
+}

README.md

@@ -0,0 +1,227 @@
+---
+license: mit
+datasets:
+- allura-org/Celeste-Filtered
+- allura-org/neon-41k
+- EVA-UNIT-01/Lilith-v0.2
+language:
+- en
+base_model:
+- THUDM/GLM-4-9B-0414
+library_name: transformers
+---
+
+<img src="image_28.png">
+<small>Image by CalamitousFelicitousness</small>
+
+---
+
+# GLM-4-9B-0414 Neon v2
+
+RP finetune of GLM-4-9B-0414. Feels nice, lots of personality, if bit quirky sometimes. Nice prose, not too Claude-ish or Gemini-ish. Doesn't seem to like too long system prompts or charcards though. Seems to like JSON formatted system prompts.
+
+Model was trained by Auri.
+
+---
+
+**Training notes**
+
+Model was trained on a dataset consisting of 77M tokens of synthetic RP and short story gen data for one epoch. Training took around 11 hours on 2xRTX 3090 workstation, generously provided by [OwenArli](https://huggingface.co/OwenArli). Went with some sane defaults for training config, QLoRA plus CCE for a nice chunk of memory usage optimization, 16k fit on 48GB nicely with some room to spare. I seem to have a problem with Eval/Loss being broken, not sure why, otherwise it trained smoothly.
+
+Huge thanks to [ArliAI](https://www.arliai.com/) for providing compute and collaborating on this run!
+
+**Format**
+
+Model responds to GLM4 instruct formatting, exactly like it's base model. Backends struggle to add BOS token automatically, so you'll need to do it yourself. Jinja template should work for chat completions.
+
+```
+[gMASK]<sop><|system|>
+{system_prompt}<|user|>
+{prompt}<|assistant|>
+```
+
+**Recommended Samplers**
+
+Nothing special, just classics.
+
+```
+Temperature - 1
+Min-P - 0.1
+Repetition Penalty - 1.03
+```
+
+[Example master import for SillyTavern (using Shingane-v1 system prompt by Steelskull)](https://huggingface.co/allura-org/GLM4-9B-Neon-v2/blob/main/GLM-Shingane-v1.json)
+
+**Running on KoboldCPP and other backends**
+
+To run GGUFs correctly, you need the most recent version of KoboldCPP, and to pass `--overridekv glm4.rope.dimension_count=int:64` to the CLI command or put `glm4.rope.dimension_count=int:64` into overridekv box in the GUI (under the Tokens tab at the very bottom).
+
+Thanks to DaringDuck and tofumagnate for info how to apply this fix.
+
+To run this model on vLLM, you'll need to build it from source from the git repo, full GLM4 support hasn't reached release yet.
+
+ExLLaMAv2 and v3 based backends, such as TabbyAPI should support the model out of the box.
+
+Latest versions of llama.cpp server should also allow running GGUFs out-of-the-box.
+
+---
+
+**Special Thanks**
+
+Once again, huge kudos to OwenArli for providing compute and helping with tuning along the way!
+
+Big thanks to Artus for providing free inference for pre-release showcase of this model!
+
+And big thanks to BeaverAI community for giving feedback and helping to figure out optimal settings!
+
+---
+
+**Training config**
+<details><summary>See Axolotl config</summary>
+
+```yaml
+# Model
+base_model: /home/owen/models/GLM-4-9B-0414
+strict: false
+model_type: AutoModelForCausalLM
+
+# Liger Kernels and CCE (optimization)
+plugins:
+  - axolotl.integrations.liger.LigerPlugin
+  - axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
+liger_rope: false
+liger_rms_norm: false
+liger_glu_activation: false
+liger_fused_linear_cross_entropy: false
+cut_cross_entropy: true
+
+# Output and HuggingFace
+output_dir: ./GLM-9B-Neon-v2
+hub_model_id: AuriAetherwiing/GLM-9B-Neon-v2-LoRA
+hf_use_auth_token: true
+hub_strategy: "all_checkpoints"
+
+# WandB
+wandb_project: allura-org
+wandb_entity:
+wandb_name: GLM-9B-Neon-v2
+
+# === Data Configuration ===
+
+# Data
+#chat_template: chatml
+#train_on_inputs: false
+group_by_length: false
+datasets:
+  - path: ./Neon/neon.jsonl
+    type: chat_template
+    field_messages: conversations
+    message_field_role: from
+    message_field_content: value
+  - path: ./Neon/S2.jsonl
+    type: chat_template
+    field_messages: conversations
+    message_field_role: from
+    message_field_content: value
+  - path: ./Neon/SystemChat_subset_filtered_sharegpt_utf8fix.jsonl
+    type: chat_template
+    field_messages: conversations
+    message_field_role: from
+    message_field_content: value
+
+dataset_prepared_path: ./lora_last_run_prepared
+
+## Evaluation
+val_set_size: 0.01
+evals_per_epoch: 2
+eval_table_size:
+eval_max_new_tokens: 128
+
+# Technical aspects
+sequence_len: 16384
+save_safetensors: true
+saves_per_epoch: 2
+logging_steps: 1
+#special_tokens:
+#  pad_token: <pad>
+# Quantization
+bf16: auto
+fp16:
+tf32: false
+## For LoRA
+load_in_8bit: false
+load_in_4bit: true
+
+# LoRA
+peft_use_rslora: false
+peft_use_dora: false # better but slower
+adapter: qlora # lora or qlora
+lora_model_dir:
+lora_r: 64 # 64 is optimal for most trains on instruct
+lora_alpha: 64
+lora_dropout: 0.1
+lora_target_linear: true
+lora_fan_in_fan_out:
+lora_target_modules:
+
+# loraplus_lr_ratio: 8 # works to converge faster but is kinda cancer bc makes model unstable
+#loraplus_lr_embedding:
+
+# Training hyperparameters
+# max_steps:
+num_epochs: 1
+
+# Anti Overfit and Stability
+weight_decay: 0.01
+max_grad_norm: 1.0
+
+## Learning Rate
+warmup_ratio: 0.05
+learning_rate: 1e-5
+lr_scheduler: rex
+#lr_scheduler_kwargs:
+#    min_lr: 0.0000024
+optimizer: adamw_torch # usually adamw_torch or paged_adamw_8bit
+
+## Batch Size
+gradient_accumulation_steps: 32      # More effective batch size - stabler train, usually. MBS also speeds it up.
+micro_batch_size: 1          # Batch size per gpu = micro_batch_size * gradient_accumulation_steps
+eval_batch_size: 1
+
+# Optimizations
+pad_to_sequence_len: true
+sample_packing: true
+eval_sample_packing: false
+flash_attention: true
+xformers_attention:
+gradient_checkpointing:
+gradient_checkpointing_kwargs:
+   use_reentrant: false
+   
+# Set to a divisor (> 1) of the number of GPUs available
+#sequence_parallel_degree: 2  # Split sequences across 4 GPUs
+# Optional; strides across the key dimension. Larger values use more memory but should make training faster.
+#heads_k_stride: 1
+# Optional; one of "varlen_llama3", "batch_ring", "batch_zigzag", "batch_stripe". Defaults to
+# "varlen_llama3" when `sample_packing: true`, and "batch_ring" otherwise.
+#ring_attn_func:
+   
+# deepspeed: /home/owen/axolotl/deepspeed_configs/zero3_bf16_cpuoffload_all.json
+
+fsdp:
+  - full_shard
+  - auto_wrap
+fsdp_config:
+  fsdp_limit_all_gathers: true
+  fsdp_sync_module_states: true
+  fsdp_offload_params: false
+  fsdp_use_orig_params: false
+  fsdp_cpu_ram_efficient_loading: true
+  fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
+  fsdp_transformer_layer_cls_to_wrap: Glm4DecoderLayer
+  fsdp_state_dict_type: FULL_STATE_DICT
+  fsdp_sharding_strategy: FULL_SHARD
+  fsdp_activation_checkpointing: true
+```
+
+</details>

config.json

@@ -0,0 +1,38 @@
+{
+    "architectures": [
+        "Glm4ForCausalLM"
+    ],
+    "attention_bias": true,
+    "attention_dropout": 0.0,
+    "eos_token_id": 151336,
+    "head_dim": 128,
+    "hidden_act": "silu",
+    "hidden_size": 4096,
+    "initializer_range": 0.02,
+    "intermediate_size": 13696,
+    "max_position_embeddings": 32768,
+    "model_type": "glm4",
+    "num_attention_heads": 32,
+    "num_hidden_layers": 40,
+    "num_key_value_heads": 2,
+    "pad_token_id": 151329,
+    "partial_rotary_factor": 0.5,
+    "rms_norm_eps": 1e-05,
+    "rope_theta": 10000.0,
+    "tie_word_embeddings": false,
+    "torch_dtype": "bfloat16",
+    "transformers_version": "4.51.3",
+    "use_cache": true,
+    "vocab_size": 151552,
+    "quantization_config": {
+        "quant_method": "exl2",
+        "version": "0.2.9",
+        "bits": 3.5,
+        "head_bits": 8,
+        "calibration": {
+            "rows": 115,
+            "length": 2048,
+            "dataset": "(default)"
+        }
+    }
+}

generation_config.json

@@ -0,0 +1,11 @@
+{
+  "_from_model_config": true,
+  "do_sample": true,
+  "eos_token_id": [
+    151329,
+    151336,
+    151338
+  ],
+  "pad_token_id": 151329,
+  "transformers_version": "4.51.3"
+}

model.safetensors.index.json

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special_tokens_map.json

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+{
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+    "<|endoftext|>",
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tokenizer_config.json

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+      "normalized": false,
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+    "<|user|>",
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+    "<|begin_of_image|>",
+    "<|end_of_image|>",
+    "<|begin_of_video|>",
+    "<|end_of_video|>"
+  ],
+  "chat_template": "[gMASK]<sop>\n{%- if tools -%}\n<|system|>\n# 可用工具\n{% for tool in tools %}\n    {%- set function = tool.function if tool.get(\"function\") else tool %}\n\n## {{ function.name }}\n\n{{ function | tojson(indent=4, ensure_ascii=False) }}\n在调用上述函数时，请使用 Json 格式表示调用的参数。\n{%- endfor %}\n{%- endif -%}\n\n{%- for msg in messages %}\n    {%- if msg.role == 'system' %}\n<|system|>\n{{ msg.content }}\n    {%- endif %}\n{%- endfor %}\n\n{%- for message in messages if message.role != 'system' %}\n    {%- set role = message['role'] %}\n    {%- set content = message['content'] %}\n    {%- set meta = message.get(\"metadata\", \"\") %}\n\n    {%- if role == 'user' %}\n<|user|>\n{{ content }}\n    {%- elif role == 'assistant' and not meta %}\n<|assistant|>\n{{ content }}\n    {%- elif role == 'assistant' and meta %}\n<|assistant|>{{ meta }}\n{{ content }}\n    {%- elif role == 'observation' %}\n<|observation|>\n{{ content }}\n    {%- endif %}\n{%- endfor %}\n{% if add_generation_prompt %}<|assistant|>{% endif %}",
+  "clean_up_tokenization_spaces": false,
+  "do_lower_case": false,
+  "eos_token": "<|user|>",
+  "extra_special_tokens": {},
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
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+  "model_max_length": 128000,
+  "pad_token": "<|endoftext|>",
+  "padding_side": "left",
+  "remove_space": false,
+  "tokenizer_class": "PreTrainedTokenizer"
+}