Upload folder using huggingface_hub

.gitattributes

@@ -33,3 +33,6 @@ 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
+.tmpUMarya filter=lfs diff=lfs merge=lfs -text
+model.safetensors.index.json filter=lfs diff=lfs merge=lfs -text

.omo/run-continuation/ses_0c21e7031ffeinIgwbwfijjAzG.json

@@ -0,0 +1,10 @@
+{
+  "sessionID": "ses_0c21e7031ffeinIgwbwfijjAzG",
+  "updatedAt": "2026-07-07T18:40:56.589Z",
+  "sources": {
+    "background-task": {
+      "state": "idle",
+      "updatedAt": "2026-07-07T18:40:56.589Z"
+    }
+  }
+}

LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2026 Zhipu AI
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

@@ -1,3 +1,64 @@
 ---
+language:
+- en
+- zh
+library_name: transformers
 license: mit
+pipeline_tag: text-generation
 ---
+
+# Sybil 0.1
+
+Sybil 0.1 is an experimental base language model derived from GLM-5.2. It is
+intended for researchers and builders who want a GLM-5.2-lineage foundation
+checkpoint for further evaluation, adaptation, and text-generation experiments.
+
+This is a base model, not an instruction-tuned assistant. Prompts should be
+designed accordingly, and downstream behavior depends heavily on sampling
+settings, prompt format, and any additional fine-tuning or alignment applied by
+the user.
+
+## Model Lineage
+
+- **Model name:** Sybil 0.1
+- **Base lineage:** GLM-5.2
+- **Model type:** Base text-generation model
+- **Languages:** English and Chinese
+- **License:** MIT
+- **Library:** Transformers-compatible GLM architecture
+
+Sybil 0.1 preserves the GLM-5.2 model family as its foundation while being
+packaged as a separate base checkpoint for experimentation.
+
+## Intended Use
+
+Sybil 0.1 is suitable for:
+
+- Research on GLM-5.2-derived base models
+- Continued pretraining or supervised adaptation
+- Prompting and sampling experiments
+- Evaluation of base-model behavior before downstream tuning
+
+It is not presented as a production assistant, safety-filtered chatbot, or
+drop-in replacement for an instruction-tuned model.
+
+## Usage Notes
+
+Use an inference stack that supports the GLM-5.2 architecture and the model's
+checkpoint format. Because this is a base model, start with conservative
+generation settings and evaluate outputs carefully for your use case.
+
+Example areas to validate before deployment include instruction following,
+factuality, multilingual behavior, long-context behavior, refusal behavior,
+domain-specific accuracy, and safety characteristics.
+
+## Evaluation
+
+No Sybil 0.1-specific benchmark results are claimed in this README. Users should
+run their own evaluations on the tasks, prompts, and inference settings relevant
+to their intended use.
+
+## Attribution
+
+Sybil 0.1 is derived from GLM-5.2. For details on the original GLM-5 model
+family, see the GLM-5 technical report and upstream project materials.

SYBIL.md

@@ -0,0 +1,45 @@
+# Sybil 0.1
+
+Derived from `zai-org/GLM-5.2-FP8` by transferring the huihui-ai GLM-5.2 abliteration
+onto the official FP8 weights.
+
+## Method (shared-subspace coefficient-replace)
+
+1. **Recover the refusal direction.** For each residual-writing target tensor, compute
+   `delta = dequant(base_fp8) - dequant(huihui_gguf)`. Per-tensor Q8_0 quant noise is
+   independent and averages out in a per-tensor-normalized delta covariance, while the
+   abliteration direction is shared across all target tensors and dominates. The top-3
+   eigenvectors form the refusal subspace `Q` (rank-1 energy ~0.57; the edit is
+   effectively rank-1, rank-3 kept to match the published spec).
+2. **Re-apply to the official weights.** For each target tensor:
+   `W_sybil = W_base - Q^T (Q W_base) + Q^T (Q W_ablit)`, i.e. replace the official
+   weight's component in `span(Q)` with huihui's component (the abliteration *amplifies*
+   this direction; it is not nulled — consistent with the huihui note that final weights
+   increase). Then requantize to block-FP8 (128x128) with error feedback so the injected
+   coefficient survives quantization.
+3. **Leave everything else untouched.** All non-target shards are hardlinked byte-identical;
+   non-target tensors inside touched shards are passed through byte-for-byte.
+
+## Target set (132 tensors)
+
+Layers **13-78** inclusive (the huihui model card states the first 12 layers and all
+expert modules are not ablated), on the residual-writing paths:
+`self_attn.o_proj.weight` (66) and `mlp.shared_experts.down_proj.weight` (66). Routed
+experts and all gate/up projections are unchanged.
+
+## Validation
+
+- Targets changed: 132/132.
+- Coefficient moved toward abliterated (dst > base): 132/132.
+- Coefficient error to abliterated reduced >65%: 129/132.
+- Mean subspace coefficient: base 8.474 -> sybil 8.717 (abliterated target 8.712).
+- Non-target tensors in touched shards: 57,039 checked, 0 mismatches.
+- Non-target shards inode/byte-identical: 73/73.
+
+## Source
+
+- Base: `zai-org/GLM-5.2-FP8`
+- Abliteration: `huihui-ai/Huihui-GLM-5.2-abliterated-GGUF` (UD-Q3_K_M; the 132 target
+  tensors are stored Q8_0 in that quant).
+
+Provenance artifacts: `sybil_provenance/` and `/home/cvm/abliterate/sybil/reports/`.

chat_template.jinja

@@ -0,0 +1,119 @@
+[gMASK]<sop>
+{%- set effective_reasoning_effort = 'high' if reasoning_effort is defined and reasoning_effort == 'high' else 'max' -%}
+{%- if (enable_thinking is not defined or enable_thinking) and effective_reasoning_effort is not none -%}<|system|>Reasoning Effort: {{ effective_reasoning_effort | capitalize }}{%- endif -%}
+{%- if tools -%}
+{%- macro tool_to_json(tool) -%}
+    {%- set ns_tool = namespace(first=true) -%}
+    {{ '{' -}}
+    {%- for k, v in tool.items() -%}
+        {%- if k != 'defer_loading' and k != 'strict' -%}
+            {%- if not ns_tool.first -%}{{- ', ' -}}{%- endif -%}
+            {%- set ns_tool.first = false -%}
+            "{{ k }}": {{ v | tojson(ensure_ascii=False) }}
+        {%- endif -%}
+    {%- endfor -%}
+    {{- '}' -}}
+{%- endmacro -%}
+<|system|>
+# Tools
+
+You may call one or more functions to assist with the user query.
+
+You are provided with function signatures within <tools></tools> XML tags:
+<tools>
+{% for tool in tools %}
+{%- if 'function' in tool -%}
+    {%- set tool = tool['function'] -%}
+{%- endif -%}
+{% if tool.defer_loading is not defined or not tool.defer_loading %}
+{{ tool_to_json(tool) }}
+{% endif %}
+{% endfor %}
+</tools>
+
+For each function call, output the function name and arguments within the following XML format:
+<tool_call>{function-name}<arg_key>{arg-key-1}</arg_key><arg_value>{arg-value-1}</arg_value><arg_key>{arg-key-2}</arg_key><arg_value>{arg-value-2}</arg_value>...</tool_call>{%- endif -%}
+{%- macro visible_text(content) -%}
+    {%- if content is string -%}
+        {{- content }}
+    {%- elif content is iterable and content is not mapping -%}
+        {%- for item in content -%}
+            {%- if item is mapping and item.type == 'text' -%}
+                {{- item.text }}
+            {%- elif item is string -%}
+                {{- item }}
+            {%- elif item is mapping and item.type in ['image', 'image_url', 'video', 'video_url', 'audio', 'audio_url', 'input_audio'] -%}
+                {%- set media_type = item.type | replace('_url', '') | replace('input_', '') -%}
+                {{- "<reminder>You are unable to process this " ~ media_type ~ " because you don't have multi-modal input ability. Try different methods.</reminder>" }}
+            {%- endif -%}
+        {%- endfor -%}
+    {%- else -%}
+        {{- content }}
+    {%- endif -%}
+{%- endmacro -%}
+{%- set ns = namespace(last_user_index=-1) -%}
+{%- for m in messages %}
+    {%- if m.role == 'user' %}
+        {%- set ns.last_user_index = loop.index0 -%}
+    {%- endif %}
+{%- endfor %}
+{%- for m in messages -%}
+{%- if m.role == 'user' -%}<|user|>{{ visible_text(m.content) }}
+{%- elif m.role == 'assistant' -%}
+<|assistant|>
+{%- set content = visible_text(m.content) %}
+{%- if m.reasoning_content is string %}
+    {%- set reasoning_content = m.reasoning_content %}
+{%- elif '</think>' in content %}
+    {%- set reasoning_content = content.split('</think>')[0].split('<think>')[-1] %}
+    {%- set content = content.split('</think>')[-1] %}
+{%- endif %}
+{%- if ((clear_thinking is defined and not clear_thinking) or loop.index0 > ns.last_user_index) and reasoning_content is defined -%}
+{{ '<think>' + reasoning_content +  '</think>'}}
+{%- else -%}
+{{ '<think></think>' }}
+{%- endif -%}
+{%- if content.strip() -%}
+{{ content.strip() }}
+{%- endif -%}
+{% if m.tool_calls %}
+{% for tc in m.tool_calls %}
+{%- if tc.function %}
+    {%- set tc = tc.function %}
+{%- endif %}
+{{- '<tool_call>' + tc.name -}}
+{% set _args = tc.arguments %}{% for k, v in _args.items() %}<arg_key>{{ k }}</arg_key><arg_value>{{ v | tojson(ensure_ascii=False) if v is not string else v }}</arg_value>{% endfor %}</tool_call>{% endfor %}
+{% endif %}
+{%- elif m.role == 'tool' -%}
+{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
+    {{- '<|observation|>' -}}
+{%- endif %}
+{%- if m.content is string -%}
+    {{- '<tool_response>' + m.content + '</tool_response>' -}}
+{%- elif m.content is iterable and m.content is not mapping and m.content and m.content.0.type == "tool_reference" -%}
+    {{- '<tool_response><tools>\n' -}}
+    {% for tr in m.content %}
+        {%- for tool in tools -%}
+            {%- if 'function' in tool -%}
+                {%- set tool = tool['function'] -%}
+            {%- endif -%}
+            {%- if tool.name == tr.name -%}
+                {{- tool_to_json(tool) + '\n' -}}
+            {%- endif -%}
+        {%- endfor -%}
+    {%- endfor -%}
+    {{- '</tools></tool_response>' -}}
+{%- elif m.content is iterable and m.content is not mapping and m.content and m.content.0 is mapping and m.content.0.output is defined -%}
+    {%- for tr in m.content -%}
+        {{- '<tool_response>' + tr.output + '</tool_response>' -}}
+    {%- endfor -%}
+{%- else -%}
+    {{- '<tool_response>' + visible_text(m.content) + '</tool_response>' -}}
+{% endif -%}
+{%- elif m.role == 'system' -%}
+<|system|>{{ visible_text(m.content) }}
+{%- endif -%}
+{%- endfor -%}
+{%- if add_generation_prompt -%}
+    <|assistant|>{{- '<think></think>' if (enable_thinking is defined and not enable_thinking) else '<think>' -}}
+{%- endif -%}

config.json

@@ -0,0 +1,776 @@
+{
+  "architectures": [
+    "GlmMoeDsaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "dtype": "bfloat16",
+  "eos_token_id": [
+    154820,
+    154827,
+    154829
+  ],
+  "ep_size": 1,
+  "first_k_dense_replace": 3,
+  "head_dim": 192,
+  "hidden_act": "silu",
+  "hidden_size": 6144,
+  "index_head_dim": 128,
+  "index_n_heads": 32,
+  "index_share_for_mtp_iteration": true,
+  "index_skip_topk_offset": 3,
+  "index_topk": 2048,
+  "index_topk_freq": 4,
+  "index_topk_pattern": null,
+  "indexer_rope_interleave": true,
+  "indexer_types": [
+    "full",
+    "full",
+    "full",
+    "shared",
+    "shared",
+    "shared",
+    "full",
+    "shared",
+    "shared",
+    "shared",
+    "full",
+    "shared",
+    "shared",
+    "shared",
+    "full",
+    "shared",
+    "shared",
+    "shared",
+    "full",
+    "shared",
+    "shared",
+    "shared",
+    "full",
+    "shared",
+    "shared",
+    "shared",
+    "full",
+    "shared",
+    "shared",
+    "shared",
+    "full",
+    "shared",
+    "shared",
+    "shared",
+    "full",
+    "shared",
+    "shared",
+    "shared",
+    "full",
+    "shared",
+    "shared",
+    "shared",
+    "full",
+    "shared",
+    "shared",
+    "shared",
+    "full",
+    "shared",
+    "shared",
+    "shared",
+    "full",
+    "shared",
+    "shared",
+    "shared",
+    "full",
+    "shared",
+    "shared",
+    "shared",
+    "full",
+    "shared",
+    "shared",
+    "shared",
+    "full",
+    "shared",
+    "shared",
+    "shared",
+    "full",
+    "shared",
+    "shared",
+    "shared",
+    "full",
+    "shared",
+    "shared",
+    "shared",
+    "full",
+    "shared",
+    "shared",
+    "shared"
+  ],
+  "initializer_range": 0.02,
+  "intermediate_size": 12288,
+  "kv_lora_rank": 512,
+  "max_position_embeddings": 1048576,
+  "mlp_layer_types": [
+    "dense",
+    "dense",
+    "dense",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse"
+  ],
+  "model_type": "glm_moe_dsa",
+  "moe_intermediate_size": 2048,
+  "moe_layer_freq": 1,
+  "moe_router_dtype": "float32",
+  "n_group": 1,
+  "n_routed_experts": 256,
+  "n_shared_experts": 1,
+  "norm_topk_prob": true,
+  "num_attention_heads": 64,
+  "num_experts_per_tok": 8,
+  "num_hidden_layers": 78,
+  "num_key_value_heads": 64,
+  "num_nextn_predict_layers": 1,
+  "pad_token_id": 154820,
+  "pretraining_tp": 1,
+  "q_lora_rank": 2048,
+  "qk_head_dim": 256,
+  "qk_nope_head_dim": 192,
+  "qk_rope_head_dim": 64,
+  "rms_norm_eps": 1e-05,
+  "rope_interleave": true,
+  "rope_parameters": {
+    "rope_theta": 8000000,
+    "rope_type": "default"
+  },
+  "routed_scaling_factor": 2.5,
+  "scoring_func": "sigmoid",
+  "tie_word_embeddings": false,
+  "topk_group": 1,
+  "topk_method": "noaux_tc",
+  "transformers_version": "5.12.0",
+  "use_cache": true,
+  "v_head_dim": 256,
+  "vocab_size": 154880,
+  "quantization_config": {
+    "activation_scheme": "dynamic",
+    "fmt": "e4m3",
+    "quant_method": "fp8",
+    "weight_block_size": [
+      128,
+      128
+    ],
+    "modules_to_not_convert": [
+      "model.layers.59.post_attention_layernorm",
+      "model.layers.47.mlp.gate.e_score_correction_bias",
+      "model.layers.71.self_attn.kv_a_layernorm",
+      "model.layers.46.mlp.gate.e_score_correction_bias",
+      "model.layers.30.self_attn.kv_a_layernorm",
+      "model.layers.23.self_attn.kv_a_layernorm",
+      "model.layers.73.mlp.gate.e_score_correction_bias",
+      "model.layers.36.mlp.gate",
+      "model.layers.12.self_attn.q_a_layernorm",
+      "model.layers.51.mlp.gate",
+      "model.layers.47.self_attn.kv_a_layernorm",
+      "model.layers.45.self_attn.q_a_layernorm",
+      "model.layers.15.self_attn.q_a_layernorm",
+      "model.layers.39.input_layernorm",
+      "model.layers.50.self_attn.kv_a_layernorm",
+      "model.layers.19.post_attention_layernorm",
+      "model.layers.71.input_layernorm",
+      "model.layers.72.self_attn.kv_a_layernorm",
+      "model.layers.70.mlp.gate",
+      "model.layers.52.input_layernorm",
+      "model.layers.78.self_attn.kv_a_layernorm",
+      "model.layers.48.post_attention_layernorm",
+      "model.layers.4.self_attn.q_a_layernorm",
+      "model.layers.62.self_attn.q_a_layernorm",
+      "model.layers.4.post_attention_layernorm",
+      "model.layers.38.self_attn.indexers_proj",
+      "model.layers.61.mlp.gate.e_score_correction_bias",
+      "model.layers.14.mlp.gate.e_score_correction_bias",
+      "model.layers.36.self_attn.kv_a_layernorm",
+      "model.layers.65.mlp.gate",
+      "model.layers.13.self_attn.kv_a_layernorm",
+      "model.layers.57.mlp.gate",
+      "model.layers.65.self_attn.kv_a_layernorm",
+      "model.layers.68.input_layernorm",
+      "model.layers.70.self_attn.kv_a_layernorm",
+      "model.layers.24.mlp.gate.e_score_correction_bias",
+      "model.layers.4.input_layernorm",
+      "model.layers.20.input_layernorm",
+      "model.layers.65.self_attn.q_a_layernorm",
+      "model.layers.38.mlp.gate",
+      "model.layers.76.mlp.gate.e_score_correction_bias",
+      "model.layers.62.input_layernorm",
+      "model.layers.45.input_layernorm",
+      "model.layers.68.post_attention_layernorm",
+      "model.layers.72.input_layernorm",
+      "model.layers.32.mlp.gate.e_score_correction_bias",
+      "model.layers.27.input_layernorm",
+      "model.layers.16.post_attention_layernorm",
+      "model.layers.35.self_attn.q_a_layernorm",
+      "model.layers.58.self_attn.indexers_proj",
+      "model.layers.3.mlp.gate.e_score_correction_bias",
+      "model.layers.49.self_attn.q_a_layernorm",
+      "model.layers.66.mlp.gate.e_score_correction_bias",
+      "model.layers.10.self_attn.q_a_layernorm",
+      "model.layers.51.mlp.gate.e_score_correction_bias",
+      "model.layers.64.self_attn.q_a_layernorm",
+      "model.layers.70.input_layernorm",
+      "model.layers.71.post_attention_layernorm",
+      "model.layers.67.post_attention_layernorm",
+      "model.layers.6.self_attn.indexer.k_norm",
+      "model.layers.3.mlp.gate",
+      "model.layers.11.mlp.gate",
+      "model.layers.17.input_layernorm",
+      "model.layers.13.mlp.gate",
+      "model.layers.15.mlp.gate",
+      "model.layers.71.self_attn.q_a_layernorm",
+      "model.layers.33.mlp.gate.e_score_correction_bias",
+      "model.layers.72.mlp.gate.e_score_correction_bias",
+      "model.layers.65.post_attention_layernorm",
+      "model.layers.78.hnorm",
+      "model.layers.40.post_attention_layernorm",
+      "model.layers.12.mlp.gate.e_score_correction_bias",
+      "model.layers.8.input_layernorm",
+      "model.layers.73.mlp.gate",
+      "model.layers.11.post_attention_layernorm",
+      "model.layers.61.input_layernorm",
+      "model.layers.14.self_attn.kv_a_layernorm",
+      "model.layers.39.self_attn.kv_a_layernorm",
+      "model.layers.70.self_attn.indexer.k_norm",
+      "model.layers.45.mlp.gate",
+      "model.layers.51.self_attn.q_a_layernorm",
+      "model.layers.64.post_attention_layernorm",
+      "model.layers.20.post_attention_layernorm",
+      "model.layers.66.self_attn.kv_a_layernorm",
+      "model.layers.10.self_attn.indexer.k_norm.bias",
+      "model.layers.23.input_layernorm",
+      "model.layers.38.self_attn.indexer.k_norm",
+      "model.layers.19.self_attn.kv_a_layernorm",
+      "model.layers.40.self_attn.q_a_layernorm",
+      "model.layers.10.self_attn.indexer.k_norm",
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