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iCoder-27B

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+ *.pt filter=lfs diff=lfs merge=lfs -text
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+ *.rar filter=lfs diff=lfs merge=lfs -text
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+ *.safetensors filter=lfs diff=lfs merge=lfs -text
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+ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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+ *.tar.* filter=lfs diff=lfs merge=lfs -text
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+ *.tar 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
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+ figures/industrial_benchmark_logo_bars.png filter=lfs diff=lfs merge=lfs -text
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+ figures/intro_pipeline.png filter=lfs diff=lfs merge=lfs -text
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+ figures/title.png filter=lfs diff=lfs merge=lfs -text
README.md ADDED
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1
+ ---
2
+ license: apache-2.0
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+ base_model:
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+ - Qwen/Qwen3.6-27B
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+ pipeline_tag: text-generation
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+ library_name: transformers
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+ tags:
8
+ - code
9
+ - rtl
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+ - verilog
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+ - gpu-kernel
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+ - triton
13
+ ---
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+
15
+ <p align="center">
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+ <img src="figures/title.png" alt="iCoder-27B" width="420">
17
+ </p>
18
+
19
+ <div align="center"><a href="https://github.com/bingreeky/iCoder"><img src="https://img.shields.io/badge/GitHub-iCoder-181717?logo=github&logoColor=white" alt="GitHub"></a> <img src="https://img.shields.io/badge/Technical%20Report-coming%20soon-9c9c9c" alt="Technical Report"></div>
20
+
21
+ iCoder-27B is a 27B-parameter model for industrial coding, covering RTL design
22
+ and GPU kernel optimization.
23
+
24
+ It is the product of an experiment in delegating model development itself.
25
+ Human experts encoded their model-development experience once, as reusable
26
+ Research Skills. From that point on an agent instantiated those Skills,
27
+ allocated resources, ran and diagnosed experiments, and revised the training
28
+ strategy. The agent coordinated a multi-stage pipeline spanning supervised
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+ fine-tuning, on-policy self-distillation, and reinforcement learning with
30
+ verifiable rewards, in which every reward comes from compiling and running the
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+ model's own output rather than from comparison against a reference text.
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+
33
+ ![Pipeline](figures/intro_pipeline.png)
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+
35
+ Despite its compact scale, iCoder-27B surpasses models with up to 59x more
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+ total parameters, including DeepSeek-V4-Pro, GLM-5.2 and Kimi-K2.6. It leads on
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+ RTLLM (68.0), ties Claude Opus 4.8 for the best TritonBench-G pass@1 (20.1),
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+ and ranks second on KernelBench L2 Fast and on CVDP. Its 61% KernelBench L1
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+ correctness is the highest of any model evaluated.
40
+
41
+ A technical report describing the recipe is in preparation.
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+
43
+ ## Results
44
+
45
+ ![Benchmarks](figures/industrial_benchmark_logo_bars.png)
46
+
47
+ Every model is evaluated through the same harness. RTL benchmarks run under the
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+ simulator each official suite specifies; kernel benchmarks compare candidate
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+ outputs against the reference implementation under matched inputs. **Bold**
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+ marks the best result in each row and *italic* the second best.
51
+
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+ | Benchmark | Metric | iCoder-27B | Qwen3.6-27B | InCoder-32B | InCoder-32B-T | DeepSeek-V4-Pro | GLM-5.2 | Kimi-K2.6 | GPT-5.5 | Claude-Opus-4.8 | Hy3 | Gemini-3.5-Flash |
53
+ |---|---|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|
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+ | VerilogEval | Spec-to-RTL avg@4 | 86.3 | 70.1 | 62.5 | 65.9 | 69.9 | 66.0 | 72.4 | **90.1** | 82.7 | 83.8 | *89.1* |
55
+ | VerilogEval | Code-complete avg@4 | *86.0* | 70.8 | 58.2 | 54.2 | 79.8 | 74.8 | 78.5 | **91.4** | 81.9 | 81.6 | 83.8 |
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+ | RTLLM | Functional avg@4 | **68.0** | 49.6 | 48.0 | 44.2 | *67.5* | 64.0 | 59.0 | 66.0 | 64.7 | 53.5 | 63.5 |
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+ | CVDP | Functional avg@5 (%) | *44.1* | 33.9 | 36.9 | 30.3 | 38.5 | 39.5 | 42.1 | 39.5 | **47.7** | 39.7 | 29.7 |
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+ | RealBench | Syntax pass@5 (%) | 61.7 | 38.3 | 60.0 | 55.0 | 36.7 | 43.3 | 58.3 | *80.0* | **83.3** | 41.7 | 68.3 |
59
+ | RealBench | Functional pass@5 (%) | 26.7 | 16.7 | **46.7** | *36.7* | 16.7 | 25.0 | 25.0 | 28.3 | *36.7* | 16.7 | 26.7 |
60
+ | ArchXBench | Functional pass@1 (%) | 49.3 | 35.2 | 36.6 | 29.6 | 50.7 | 50.7 | 42.3 | **56.3** | *54.9* | 47.9 | 50.7 |
61
+ | KernelBench L1 | Compiled (%) | 95 | 87 | 88 | 85 | 93 | *96* | 93 | **98** | 95 | 94 | 94 |
62
+ | KernelBench L1 | Correct (%) | **61** | 32 | 51 | 47 | 32 | 50 | 32 | 43 | *55* | 42 | 45 |
63
+ | KernelBench L1 | Fast (%) | 25 | 12 | 18 | 18 | 13 | *26* | 5 | 22 | **30** | 21 | 23 |
64
+ | KernelBench L2 | Compiled (%) | 97 | 89 | 90 | 93 | 91 | 98 | 84 | **100** | 97 | 98 | *99* |
65
+ | KernelBench L2 | Correct (%) | *74* | 28 | 65 | 63 | 40 | 40 | 17 | 41 | 70 | 56 | **78** |
66
+ | KernelBench L2 | Fast (%) | *40* | 17 | 14 | 15 | 25 | 30 | 7 | 24 | 37 | 29 | **47** |
67
+ | KernelBench L3 | Compiled (%) | 90 | 86 | 60 | 60 | 86 | 90 | 82 | **100** | 84 | *98* | **100** |
68
+ | KernelBench L3 | Correct (%) | 34 | 12 | 30 | 20 | 4 | 30 | 18 | 38 | *40* | 18 | **58** |
69
+ | KernelBench L3 | Fast (%) | 10 | 4 | **14** | *12* | 2 | 0 | 0 | 6 | 8 | 2 | **14** |
70
+ | TritonBench-G | Correctness pass@1 (%) | **20.1** | 11.4 | 17.9 | 18.5 | 19.0 | 19.0 | 19.0 | *19.5* | **20.1** | *19.5* | 14.9 |
71
+
72
+ ## Usage
73
+
74
+ ```python
75
+ from transformers import AutoModelForCausalLM, AutoTokenizer
76
+
77
+ model_id = "i-Coder/iCoder-27B"
78
+ tokenizer = AutoTokenizer.from_pretrained(model_id)
79
+ model = AutoModelForCausalLM.from_pretrained(
80
+ model_id, dtype="auto", device_map="auto"
81
+ )
82
+
83
+ messages = [{"role": "user", "content": "Write a 4-bit synchronous up counter with active-low reset in Verilog."}]
84
+ text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
85
+ inputs = tokenizer([text], return_tensors="pt").to(model.device)
86
+ out = model.generate(**inputs, max_new_tokens=2048)
87
+ print(tokenizer.decode(out[0][inputs.input_ids.shape[-1]:], skip_special_tokens=True))
88
+ ```
89
+
90
+ ## License
91
+
92
+ Apache-2.0, inherited from the base model, Qwen3.6-27B.
chat_template.jinja ADDED
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1
+ {%- set image_count = namespace(value=0) %}
2
+ {%- set video_count = namespace(value=0) %}
3
+ {%- macro render_content(content, do_vision_count, is_system_content=false) %}
4
+ {%- if content is string %}
5
+ {{- content }}
6
+ {%- elif content is iterable and content is not mapping %}
7
+ {%- for item in content %}
8
+ {%- if 'image' in item or 'image_url' in item or item.type == 'image' %}
9
+ {%- if is_system_content %}
10
+ {{- raise_exception('System message cannot contain images.') }}
11
+ {%- endif %}
12
+ {%- if do_vision_count %}
13
+ {%- set image_count.value = image_count.value + 1 %}
14
+ {%- endif %}
15
+ {%- if add_vision_id %}
16
+ {{- 'Picture ' ~ image_count.value ~ ': ' }}
17
+ {%- endif %}
18
+ {{- '<|vision_start|><|image_pad|><|vision_end|>' }}
19
+ {%- elif 'video' in item or item.type == 'video' %}
20
+ {%- if is_system_content %}
21
+ {{- raise_exception('System message cannot contain videos.') }}
22
+ {%- endif %}
23
+ {%- if do_vision_count %}
24
+ {%- set video_count.value = video_count.value + 1 %}
25
+ {%- endif %}
26
+ {%- if add_vision_id %}
27
+ {{- 'Video ' ~ video_count.value ~ ': ' }}
28
+ {%- endif %}
29
+ {{- '<|vision_start|><|video_pad|><|vision_end|>' }}
30
+ {%- elif 'text' in item %}
31
+ {{- item.text }}
32
+ {%- else %}
33
+ {{- raise_exception('Unexpected item type in content.') }}
34
+ {%- endif %}
35
+ {%- endfor %}
36
+ {%- elif content is none or content is undefined %}
37
+ {{- '' }}
38
+ {%- else %}
39
+ {{- raise_exception('Unexpected content type.') }}
40
+ {%- endif %}
41
+ {%- endmacro %}
42
+ {%- if not messages %}
43
+ {{- raise_exception('No messages provided.') }}
44
+ {%- endif %}
45
+ {%- if tools and tools is iterable and tools is not mapping %}
46
+ {{- '<|im_start|>system\n' }}
47
+ {{- "# Tools\n\nYou have access to the following functions:\n\n<tools>" }}
48
+ {%- for tool in tools %}
49
+ {{- "\n" }}
50
+ {{- tool | tojson }}
51
+ {%- endfor %}
52
+ {{- "\n</tools>" }}
53
+ {{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\n- Required parameters MUST be specified\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\n</IMPORTANT>' }}
54
+ {%- if messages[0].role == 'system' %}
55
+ {%- set content = render_content(messages[0].content, false, true)|trim %}
56
+ {%- if content %}
57
+ {{- '\n\n' + content }}
58
+ {%- endif %}
59
+ {%- endif %}
60
+ {{- '<|im_end|>\n' }}
61
+ {%- else %}
62
+ {%- if messages[0].role == 'system' %}
63
+ {%- set content = render_content(messages[0].content, false, true)|trim %}
64
+ {{- '<|im_start|>system\n' + content + '<|im_end|>\n' }}
65
+ {%- endif %}
66
+ {%- endif %}
67
+ {%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
68
+ {%- for message in messages[::-1] %}
69
+ {%- set index = (messages|length - 1) - loop.index0 %}
70
+ {%- if ns.multi_step_tool and message.role == "user" %}
71
+ {%- set content = render_content(message.content, false)|trim %}
72
+ {%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
73
+ {%- set ns.multi_step_tool = false %}
74
+ {%- set ns.last_query_index = index %}
75
+ {%- endif %}
76
+ {%- endif %}
77
+ {%- endfor %}
78
+ {%- if ns.multi_step_tool %}
79
+ {{- raise_exception('No user query found in messages.') }}
80
+ {%- endif %}
81
+ {%- for message in messages %}
82
+ {%- set content = render_content(message.content, true)|trim %}
83
+ {%- if message.role == "system" %}
84
+ {%- if not loop.first %}
85
+ {{- raise_exception('System message must be at the beginning.') }}
86
+ {%- endif %}
87
+ {%- elif message.role == "user" %}
88
+ {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
89
+ {%- elif message.role == "assistant" %}
90
+ {%- set reasoning_content = '' %}
91
+ {%- if message.reasoning_content is string %}
92
+ {%- set reasoning_content = message.reasoning_content %}
93
+ {%- else %}
94
+ {%- if '</think>' in content %}
95
+ {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
96
+ {%- set content = content.split('</think>')[-1].lstrip('\n') %}
97
+ {%- endif %}
98
+ {%- endif %}
99
+ {%- set reasoning_content = reasoning_content|trim %}
100
+ {%- if (preserve_thinking is defined and preserve_thinking is true) or (loop.index0 > ns.last_query_index) %}
101
+ {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
102
+ {%- else %}
103
+ {{- '<|im_start|>' + message.role + '\n' + content }}
104
+ {%- endif %}
105
+ {%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}
106
+ {%- for tool_call in message.tool_calls %}
107
+ {%- if tool_call.function is defined %}
108
+ {%- set tool_call = tool_call.function %}
109
+ {%- endif %}
110
+ {%- if loop.first %}
111
+ {%- if content|trim %}
112
+ {{- '\n\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
113
+ {%- else %}
114
+ {{- '<tool_call>\n<function=' + tool_call.name + '>\n' }}
115
+ {%- endif %}
116
+ {%- else %}
117
+ {{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
118
+ {%- endif %}
119
+ {%- if tool_call.arguments is defined %}
120
+ {%- for args_name, args_value in tool_call.arguments|items %}
121
+ {{- '<parameter=' + args_name + '>\n' }}
122
+ {%- set args_value = args_value | string if args_value is string else args_value | tojson | safe %}
123
+ {{- args_value }}
124
+ {{- '\n</parameter>\n' }}
125
+ {%- endfor %}
126
+ {%- endif %}
127
+ {{- '</function>\n</tool_call>' }}
128
+ {%- endfor %}
129
+ {%- endif %}
130
+ {{- '<|im_end|>\n' }}
131
+ {%- elif message.role == "tool" %}
132
+ {%- if loop.previtem and loop.previtem.role != "tool" %}
133
+ {{- '<|im_start|>user' }}
134
+ {%- endif %}
135
+ {{- '\n<tool_response>\n' }}
136
+ {{- content }}
137
+ {{- '\n</tool_response>' }}
138
+ {%- if not loop.last and loop.nextitem.role != "tool" %}
139
+ {{- '<|im_end|>\n' }}
140
+ {%- elif loop.last %}
141
+ {{- '<|im_end|>\n' }}
142
+ {%- endif %}
143
+ {%- else %}
144
+ {{- raise_exception('Unexpected message role.') }}
145
+ {%- endif %}
146
+ {%- endfor %}
147
+ {%- if add_generation_prompt %}
148
+ {{- '<|im_start|>assistant\n' }}
149
+ {%- if enable_thinking is defined and enable_thinking is false %}
150
+ {{- '<think>\n\n</think>\n\n' }}
151
+ {%- else %}
152
+ {{- '<think>\n' }}
153
+ {%- endif %}
154
+ {%- endif %}
config.json ADDED
@@ -0,0 +1,146 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "architectures": [
3
+ "Qwen3_5ForConditionalGeneration"
4
+ ],
5
+ "bos_token_id": null,
6
+ "dtype": "bfloat16",
7
+ "eos_token_id": 248046,
8
+ "hidden_size": 5120,
9
+ "image_token_id": 248056,
10
+ "language_model_only": false,
11
+ "model_type": "qwen3_5",
12
+ "pad_token_id": 248044,
13
+ "text_config": {
14
+ "attention_bias": false,
15
+ "attention_dropout": 0.0,
16
+ "attn_output_gate": true,
17
+ "bos_token_id": 248044,
18
+ "dtype": "bfloat16",
19
+ "eos_token_id": 248044,
20
+ "full_attention_interval": 4,
21
+ "head_dim": 256,
22
+ "hidden_act": "silu",
23
+ "hidden_size": 5120,
24
+ "initializer_range": 0.02,
25
+ "intermediate_size": 17408,
26
+ "layer_types": [
27
+ "linear_attention",
28
+ "linear_attention",
29
+ "linear_attention",
30
+ "full_attention",
31
+ "linear_attention",
32
+ "linear_attention",
33
+ "linear_attention",
34
+ "full_attention",
35
+ "linear_attention",
36
+ "linear_attention",
37
+ "linear_attention",
38
+ "full_attention",
39
+ "linear_attention",
40
+ "linear_attention",
41
+ "linear_attention",
42
+ "full_attention",
43
+ "linear_attention",
44
+ "linear_attention",
45
+ "linear_attention",
46
+ "full_attention",
47
+ "linear_attention",
48
+ "linear_attention",
49
+ "linear_attention",
50
+ "full_attention",
51
+ "linear_attention",
52
+ "linear_attention",
53
+ "linear_attention",
54
+ "full_attention",
55
+ "linear_attention",
56
+ "linear_attention",
57
+ "linear_attention",
58
+ "full_attention",
59
+ "linear_attention",
60
+ "linear_attention",
61
+ "linear_attention",
62
+ "full_attention",
63
+ "linear_attention",
64
+ "linear_attention",
65
+ "linear_attention",
66
+ "full_attention",
67
+ "linear_attention",
68
+ "linear_attention",
69
+ "linear_attention",
70
+ "full_attention",
71
+ "linear_attention",
72
+ "linear_attention",
73
+ "linear_attention",
74
+ "full_attention",
75
+ "linear_attention",
76
+ "linear_attention",
77
+ "linear_attention",
78
+ "full_attention",
79
+ "linear_attention",
80
+ "linear_attention",
81
+ "linear_attention",
82
+ "full_attention",
83
+ "linear_attention",
84
+ "linear_attention",
85
+ "linear_attention",
86
+ "full_attention",
87
+ "linear_attention",
88
+ "linear_attention",
89
+ "linear_attention",
90
+ "full_attention"
91
+ ],
92
+ "linear_conv_kernel_dim": 4,
93
+ "linear_key_head_dim": 128,
94
+ "linear_num_key_heads": 16,
95
+ "linear_num_value_heads": 48,
96
+ "linear_value_head_dim": 128,
97
+ "mamba_ssm_dtype": "float32",
98
+ "max_position_embeddings": 262144,
99
+ "model_type": "qwen3_5_text",
100
+ "mtp_num_hidden_layers": 0,
101
+ "mtp_use_dedicated_embeddings": false,
102
+ "num_attention_heads": 24,
103
+ "num_hidden_layers": 64,
104
+ "num_key_value_heads": 4,
105
+ "output_gate_type": "swish",
106
+ "pad_token_id": null,
107
+ "partial_rotary_factor": 0.25,
108
+ "rms_norm_eps": 1e-06,
109
+ "rope_parameters": {
110
+ "mrope_interleaved": true,
111
+ "mrope_section": [
112
+ 11,
113
+ 11,
114
+ 10
115
+ ],
116
+ "partial_rotary_factor": 0.25,
117
+ "rope_theta": 10000000,
118
+ "rope_type": "default"
119
+ },
120
+ "tie_word_embeddings": false,
121
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