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  1. .gitattributes +1 -0
  2. README.md +73 -0
  3. added_tokens.json +28 -0
  4. chat_template.jinja +61 -0
  5. config.json +94 -0
  6. generation_config.json +13 -0
  7. merges.txt +0 -0
  8. model-00001-of-00032.safetensors +3 -0
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  42. tokenizer.json +3 -0
  43. tokenizer_config.json +239 -0
  44. vocab.json +0 -0
.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ tokenizer.json filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,73 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
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+ license: apache-2.0
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+ base_model: Qwen/Qwen3-Next-80B-A3B-Instruct
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+ tags:
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+ - merge
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+ - lora
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+ - qwen3
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+ - instruct
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+ library_name: transformers
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+ ---
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+
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+ # sf-diogenes-v0.1
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+
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+ This model is a merge of the [Qwen/Qwen3-Next-80B-A3B-Instruct](https://huggingface.co/Qwen/Qwen3-Next-80B-A3B-Instruct) base model with the [urm3l/diogenes-v.01-lora-adapter](https://huggingface.co/urm3l/diogenes-v.01-lora-adapter) LoRA adapter.
15
+
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+ ## Model Details
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+
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+ - **Base Model**: Qwen/Qwen3-Next-80B-A3B-Instruct
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+ - **LoRA Adapter**: urm3l/diogenes-v.01-lora-adapter
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+ - **Merge Date**: 2025-11-01
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+ - **Model Size**: ~80B parameters
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+ - **Precision**: BF16
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+
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+ ## Usage
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+
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+ ```python
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+
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+ model = AutoModelForCausalLM.from_pretrained(
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+ "urm3l/sf-diogenes-v0.1",
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+ torch_dtype="auto",
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+ device_map="auto",
33
+ trust_remote_code=True
34
+ )
35
+
36
+ tokenizer = AutoTokenizer.from_pretrained(
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+ "urm3l/sf-diogenes-v0.1",
38
+ trust_remote_code=True
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+ )
40
+
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+ messages = [
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+ {"role": "system", "content": "You are a helpful assistant."},
43
+ {"role": "user", "content": "Hello!"}
44
+ ]
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+
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+ text = tokenizer.apply_chat_template(
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+ messages,
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+ tokenize=False,
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+ add_generation_prompt=True
50
+ )
51
+
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+ inputs = tokenizer(text, return_tensors="pt").to(model.device)
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+ outputs = model.generate(**inputs, max_new_tokens=512)
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+ print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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+ ```
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+
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+ ## Training Details
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+
59
+ This model was fine-tuned using LoRA (Low-Rank Adaptation). For training details, see the [adapter repository](https://huggingface.co/urm3l/diogenes-v.01-lora-adapter).
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+
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+ ## Limitations
62
+
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+ - This is a large language model and may produce incorrect or biased outputs
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+ - Should not be used for high-stakes decision making without human oversight
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+ - May require significant computational resources for inference
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+
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+ ## License
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+
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+ This model inherits the license from the base model: Apache 2.0
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+
71
+ ## Citation
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+
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+ If you use this model, please cite the original Qwen3 paper and acknowledge the LoRA fine-tuning.
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chat_template.jinja ADDED
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+ {%- if tools %}
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+ {{- '<|im_start|>system\n' }}
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+ {%- if messages[0].role == 'system' %}
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+ {{- messages[0].content + '\n\n' }}
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+ {%- endif %}
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+ {{- "# 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>" }}
7
+ {%- for tool in tools %}
8
+ {{- "\n" }}
9
+ {{- tool | tojson }}
10
+ {%- endfor %}
11
+ {{- "\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" }}
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+ {%- else %}
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+ {%- if messages[0].role == 'system' %}
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+ {{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
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+ {%- endif %}
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+ {%- endif %}
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+ {%- for message in messages %}
18
+ {%- if message.content is string %}
19
+ {%- set content = message.content %}
20
+ {%- else %}
21
+ {%- set content = '' %}
22
+ {%- endif %}
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+ {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
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+ {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
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+ {%- elif message.role == "assistant" %}
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+ {{- '<|im_start|>' + message.role + '\n' + content }}
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+ {%- if message.tool_calls %}
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+ {%- for tool_call in message.tool_calls %}
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+ {%- if (loop.first and content) or (not loop.first) %}
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+ {{- '\n' }}
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+ {%- endif %}
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+ {%- if tool_call.function %}
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+ {%- set tool_call = tool_call.function %}
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+ {%- endif %}
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+ {{- '<tool_call>\n{"name": "' }}
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+ {{- tool_call.name }}
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+ {{- '", "arguments": ' }}
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+ {%- if tool_call.arguments is string %}
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+ {{- tool_call.arguments }}
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+ {%- else %}
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+ {{- tool_call.arguments | tojson }}
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+ {%- endif %}
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+ {{- '}\n</tool_call>' }}
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+ {%- endfor %}
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+ {%- endif %}
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+ {{- '<|im_end|>\n' }}
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+ {%- elif message.role == "tool" %}
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+ {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
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+ {{- '<|im_start|>user' }}
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+ {%- endif %}
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+ {{- '\n<tool_response>\n' }}
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+ {{- content }}
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+ {{- '\n</tool_response>' }}
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+ {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
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+ {{- '<|im_end|>\n' }}
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+ {%- endif %}
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+ {%- endif %}
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+ {%- endfor %}
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+ {%- if add_generation_prompt %}
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+ {{- '<|im_start|>assistant\n' }}
61
+ {%- endif %}
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+ "architectures": [
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+ "hidden_size": 2048,
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+ "linear_attention",
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+ "linear_attention",
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+ "linear_attention",
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+ "full_attention",
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+ "linear_attention",
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+ "full_attention",
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+ "linear_attention",
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+ "linear_attention",
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+ "linear_attention",
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+ ],
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+ "linear_conv_kernel_dim": 4,
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+ "linear_key_head_dim": 128,
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+ "linear_num_key_heads": 16,
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+ "linear_num_value_heads": 32,
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+ "linear_value_head_dim": 128,
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+ "max_position_embeddings": 262144,
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+ "mlp_only_layers": [],
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+ "model_type": "qwen3_next",
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+ "moe_intermediate_size": 512,
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+ "norm_topk_prob": true,
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+ "num_attention_heads": 16,
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+ "num_experts": 512,
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+ "num_experts_per_tok": 10,
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+ "num_hidden_layers": 48,
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+ "num_key_value_heads": 2,
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+ "output_router_logits": false,
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+ "partial_rotary_factor": 0.25,
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+ "rms_norm_eps": 1e-06,
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+ "rope_scaling": null,
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+ "rope_theta": 10000000,
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+ "router_aux_loss_coef": 0.001,
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+ "shared_expert_intermediate_size": 512,
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+ "tie_word_embeddings": false,
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+ "transformers_version": "4.57.1",
91
+ "use_cache": true,
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+ "use_sliding_window": false,
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+ "vocab_size": 151936
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+ }
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