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Improve language tag

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Hi! As the model is multilingual, this is a PR to add other languages than English to the language tag to improve the referencing. Note that 29 languages are announced in the README, but only 13 are explicitly listed. I was therefore only able to add these 13 languages.

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  1. README.md +208 -196
README.md CHANGED
@@ -1,197 +1,209 @@
1
- ---
2
- license: apache-2.0
3
- license_link: https://huggingface.co/Qwen/Qwen2.5-14B-Instruct/blob/main/LICENSE
4
- language:
5
- - en
6
- pipeline_tag: text-generation
7
- base_model: Qwen/Qwen2.5-14B
8
- tags:
9
- - chat
10
- - linkedin
11
- library_name: transformers
12
- ---
13
- # LinkedQwen2.5-14B-Instruct: Fine-tuned LinkedIn Post Generator
14
- ## Model Details
15
- * **Model Name:** jacobpwarren/LinkedQwen2.5-14B-Instruct
16
- * **Base Model:** ~[Qwen2.5-14B-Instruct](https://huggingface.co/Qwen/Qwen2.5-14B-Instruct)~
17
- * **Framework:** Built using the Emulate Framework
18
- * **License:** Apache-2.0 (inherited from base model)
19
- * **Fine-tuning Focus:** LinkedIn post generation with custom writing style parameters
20
- * **Languages Supported:** English (primary), plus 28+ languages from base model
21
-
22
- ## Model Description
23
- LinkedQwen2.5-14B-Instruct is a specialized language model fine-tuned on the Qwen2.5-14B-Instruct base for generating high-quality LinkedIn posts with customizable writing styles. The model can produce various post structures while adhering to specific writing patterns, tones, and stylistic features derived from analysis of successful LinkedIn content.
24
- ## Emulate Framework Implementation
25
- This model is a practical demonstration of the Emulate Framework in action - a methodology that transforms expert knowledge and workflows into defensible AI capabilities that preserve unique competitive advantages. Unlike generic implementations, LinkedQwen2.5-14B-Instruct was built by:
26
- 1. **Reverse-engineering expert workflows** rather than starting with available data
27
- 2. **Capturing writing style fingerprints** including sentence structure, vocabulary patterns, and narrative flow
28
- 3. **Developing differentiated features** that preserve the unique elements of successful LinkedIn content
29
- 4. **Creating end-to-end automation** that completes valuable processes rather than just providing information
30
- The model represents the full execution of the Emulate process, including workflow decomposition, expert style fingerprinting, feature engineering, and systematic validation against business metrics.
31
-
32
- To learn more about fine-tuning competitively differentiated models, visit https://emulateframework.ai.
33
- ## Intended Use
34
- This model is designed for:
35
- * Content creators seeking to generate professional LinkedIn posts
36
- * Marketing professionals developing social media content
37
- * Individuals looking to improve their LinkedIn presence with stylistically consistent posts
38
- * Teams wanting to maintain brand voice across LinkedIn communications
39
- ## Base Model: Qwen2.5-14B-Instruct
40
- The fine-tuning builds upon Qwen2.5-14B-Instruct, which features:
41
- * 14.7B parameters (13.1B non-embedding)
42
- * Causal language model architecture with RoPE, SwiGLU, RMSNorm, and Attention QKV bias
43
- * 48 layers with 40 attention heads for Q and 8 for KV
44
- * Context length support up to 131,072 tokens with generation capability of 8,192 tokens
45
- * Significant improvements in instruction following and generating structured outputs
46
- ## Fine-tuning Dataset
47
- The model was fine-tuned on a dataset of high-performing LinkedIn posts, analyzed for various writing style features including:
48
- * Sentence structure patterns
49
- * Vocabulary richness
50
- * Line break usage
51
- * Punctuation patterns
52
- * Bullet styles
53
- * Topic flow and shifts
54
- * Narrative structure
55
- * Pacing and sentiment arcs
56
- ## Prompt Template
57
- The model accepts stylized prompts in the following format:
58
- ````
59
- # Request
60
- Create a LinkedIn post that **[structure type]** **on the topic of**: `[topic]`
61
-
62
- ### Key Message
63
- ```
64
- [opinion] [context]
65
- ```
66
-
67
- ### Writing Constraints
68
- - **Suggested Post Length**: [max_length]
69
- - **Emoji Usage**: [emoji_usage]
70
- - **Tone**: [tone]
71
-
72
- ### Writing Style Features
73
- - **Sentence Structure**: [sentence_structure_description]
74
- - **Vocabulary Usage**: [vocabulary_usage_description]
75
- - **Common Phrases**: [common_phrases_description]
76
- - **Section Divider**: [divider_style]
77
- - **Line Break Usage**: [line_break_description]
78
- - **Punctuation**: [punctuation_description]
79
- - **Bullet Styles**: [bullet_styles_description]
80
- - **Topic Shifts**: [topic_shifts_description]
81
- - **Narrative Flow**: [narrative_flow_description]
82
- - **Pacing**: [pacing_description]
83
- - **Sentiment Arc**: [sentiment_arc_description]
84
- - **Profanity Level**: [profanity]
85
- ````
86
- # Parameters and Variables
87
- ### Required Parameters
88
- | Parameter | Type | Description | Possible Values |
89
- |:-----------:|:----------:|:-----------------------------------:|:------------------------------------------------------------:|
90
- | structure | String | Post structure type | "instructional", "reflective", "inspirational", "controversial", "insightful", "comparative", "announcement" |
91
- | topic | Short text | Main subject of the post | Open-ended |
92
- | opinion | Short text | The user's viewpoint | Open-ended |
93
- | context | Long text | Background information for the post | Open-ended |
94
- | max_length | String | Target length for the post | "Up to 750 characters long", "Between 750 and 1,500 characters long", "Between 1,500 and 3,000 characters long" |
95
- | emoji_usage | String | Level of emoji inclusion | "none", "very low", "low", "medium", "high", "extreme" |
96
- | tone | String | Overall emotional register | "adventurous", "artistic", "assertive", "authoritative", "bold", "bright", "calm", "capable", "caring", "casual", "charming", "cheerful", "clever", "cocky", "colorful", "comfortable", "conversational", "creative", "daring", "delightful", "detailed", "dramatic", "dry", "eccentric", "elegant", "endearing", "energetic", "engaging", "exciting", "fabulous", "fancy", "fierce", "formal", "friendly", "fun", "futuristic", "glamorous", "honorable", "industrial", "informative", "inspiring", "intense", "inviting", "lively", "natural", "no-nonsense", "persuasive", "playful", "powerful", "professional", "quirky", "rebellious", "reliable", "sarcastic", "savvy", "scholarly", "secure", "serious", "silly", "sleek", "smart", "soothing", "sophisticated", "stable", "stimulating", "strong", "swanky", "tasteful", "thoughtful", "trustworthy", "unconventional", "unique", "upbeat", "versatile", "whimsical", "witty" |
97
- ### Optional Writing Style Features
98
- | Feature | Type | Description |
99
- |:-:|:-:|:-:|
100
- | sentence_structure | Array | Lengths of sentences, analyzed for patterns and described |
101
- | vocabulary_usage | Float | Ratio of unique words to total words, described in qualitative terms |
102
- | common_phrases | Array | Distinctive phrases identified in the writing style |
103
- | divider_style | String | Character pattern used to separate sections |
104
- | line_breaks | Integer | Count of line breaks, with qualitative description |
105
- | punctuation_usage | Object | Frequency of various punctuation marks |
106
- | bullet_styles | String | Type of bullet point formatting |
107
- | topic_shifts | Array | Indicators of subject changes throughout the post |
108
- | flow | Array | Narrative progression patterns |
109
- | pacing | String | Rhythm of the content delivery |
110
- | sentiment_arc | String | Emotional progression pattern |
111
- | profanity | String | Level of profanity allowed |
112
- ## Style Feature Descriptions
113
- ### Sentence Structure
114
- Based on analysis of sentence lengths, classified as:
115
- * "Short sentences, suggesting brevity and conciseness."
116
- * "Long and complex sentences, indicating a detailed and elaborate style."
117
- * "A mix of short and long sentences, showing a balanced style."
118
- ### Vocabulary Usage
119
- Calculated as a ratio of unique words to total words:
120
- * 50% unique: "A rich vocabulary, showcasing extensive language use and depth."
121
- * 35% unique: "A developed vocabulary, indicating a wide range of language and expression."
122
- * 25% unique: "A normal vocabulary, reflecting a balanced and versatile use of language."
123
- * 15% unique: "A conservative vocabulary, suggesting a focused and deliberate choice of words."
124
- * ≤15% unique: "A very narrow vocabulary, highlighting a specific and targeted use of language."
125
- ### Line Break Usage
126
- Based on frequency and average density:
127
- * No breaks: "No line breaks, indicating a continuous block of text."
128
- * Many breaks: "Frequent line breaks, contributing to an easy-to-read structure."
129
- * Few breaks: "Fewer line breaks, indicating a more compact writing style."
130
- * Moderate: "A moderate number of line breaks, balancing readability and density."
131
- ### Punctuation
132
- Analysis of punctuation frequency relative to text length, with descriptions like:
133
- * "Heavy use of periods/commas/exclamation marks/question marks/semicolons."
134
- * "Regular use of periods/commas/exclamation marks/question marks/semicolons."
135
- * "Standard punctuation usage."
136
- ### Bullet Styles
137
- Categorized as:
138
- * Various symbol types: "-", "•", "#", "1.", "a.", etc.
139
- * "Differing Emojis": Using various emojis as bullet points
140
- * "EmojiBullets": Multiple emojis as bullets
141
- * "Mixed Bullet Styles": Multiple formatting approaches
142
- ### Topic Shifts
143
- Based on semantic shift analysis between segments:
144
- * Dynamic (>0.8): "Dynamic topic shifts, showing a highly versatile and engaging writing style."
145
- * Regular (>0.6): "Regular topic shifts, reflecting a balanced and varied approach."
146
- * Moderate (>0.4): "Moderate topic shifts, indicating a well-rounded but focused narrative."
147
- * Conservative (>0.2): "Conservative topic shifts, suggesting a cautious approach to topic changes."
148
- * Consistent (≤0.2): "Consistent topic focus, highlighting a deep and thorough exploration of subjects."
149
- ### Narrative Flow
150
- Captured as a sequence of content structure types:
151
- * "Introduction/Setup"
152
- * "Conflict/Resolution Point"
153
- * "Introduction/Development"
154
- * "Transition/Reflection"
155
- ### Pacing
156
- Classified as:
157
- * "Fast"
158
- * "Slow"
159
- * "Variable"
160
- * "Dynamic"
161
- * "Moderate"
162
- * "Short/Not Enough Data" (if <3 sentences)
163
- ### Sentiment Arc
164
- Progression of emotional tone:
165
- * "Upward Trend": Increasingly positive
166
- * "Downward Trend": Increasingly negative
167
- * "Stable": Consistent emotional tone
168
- * "Complex/Variable": Multiple shifts
169
- * "Short/Not Enough Data for Arc": Insufficient for analysis
170
- ## Limitations
171
- * The model inherits the limitations of the base Qwen2.5-14B-Instruct model
172
- * Style analysis is most accurate for English-language content
173
- * Certain combinations of style parameters may produce inconsistent results
174
- * Performance may vary for highly technical or specialized industry topics
175
- * Not all writing style features may be represented in generated output with equal fidelity
176
- ## Ethical Considerations
177
- * The model should not be used to generate misleading or false professional information
178
- * Users should verify factual claims in generated content before publishing on LinkedIn
179
- * Consideration should be given to professional norms and cultural sensitivities in different industries and regions
180
- ## Citation
181
- ```
182
- @misc{LinkedQwen2.5-14B-Instruct,
183
- title = {LinkedQwen2.5-14B-Instruct: Fine-tuned LinkedIn Post Generator},
184
- url = {https://huggingface.co/jacobpwarren/LinkedQwen2.5-14B-Instruct},
185
- author = {Jacob Warren},
186
- year = {2025},
187
- month = {April}
188
- }
189
-
190
- @misc{qwen2.5,
191
- title = {Qwen2.5: A Party of Foundation Models},
192
- url = {https://qwenlm.github.io/blog/qwen2.5/},
193
- author = {Qwen Team},
194
- month = {September},
195
- year = {2024}
196
- }
 
 
 
 
 
 
 
 
 
 
 
 
197
  ```
 
1
+ ---
2
+ license: apache-2.0
3
+ license_link: https://huggingface.co/Qwen/Qwen2.5-14B-Instruct/blob/main/LICENSE
4
+ language:
5
+ - zho
6
+ - eng
7
+ - fra
8
+ - spa
9
+ - por
10
+ - deu
11
+ - ita
12
+ - rus
13
+ - jpn
14
+ - kor
15
+ - vie
16
+ - tha
17
+ - ara
18
+ pipeline_tag: text-generation
19
+ base_model: Qwen/Qwen2.5-14B
20
+ tags:
21
+ - chat
22
+ - linkedin
23
+ library_name: transformers
24
+ ---
25
+ # LinkedQwen2.5-14B-Instruct: Fine-tuned LinkedIn Post Generator
26
+ ## Model Details
27
+ * **Model Name:** jacobpwarren/LinkedQwen2.5-14B-Instruct
28
+ * **Base Model:** ~[Qwen2.5-14B-Instruct](https://huggingface.co/Qwen/Qwen2.5-14B-Instruct)~
29
+ * **Framework:** Built using the Emulate Framework
30
+ * **License:** Apache-2.0 (inherited from base model)
31
+ * **Fine-tuning Focus:** LinkedIn post generation with custom writing style parameters
32
+ * **Languages Supported:** English (primary), plus 28+ languages from base model
33
+
34
+ ## Model Description
35
+ LinkedQwen2.5-14B-Instruct is a specialized language model fine-tuned on the Qwen2.5-14B-Instruct base for generating high-quality LinkedIn posts with customizable writing styles. The model can produce various post structures while adhering to specific writing patterns, tones, and stylistic features derived from analysis of successful LinkedIn content.
36
+ ## Emulate Framework Implementation
37
+ This model is a practical demonstration of the Emulate Framework in action - a methodology that transforms expert knowledge and workflows into defensible AI capabilities that preserve unique competitive advantages. Unlike generic implementations, LinkedQwen2.5-14B-Instruct was built by:
38
+ 1. **Reverse-engineering expert workflows** rather than starting with available data
39
+ 2. **Capturing writing style fingerprints** including sentence structure, vocabulary patterns, and narrative flow
40
+ 3. **Developing differentiated features** that preserve the unique elements of successful LinkedIn content
41
+ 4. **Creating end-to-end automation** that completes valuable processes rather than just providing information
42
+ The model represents the full execution of the Emulate process, including workflow decomposition, expert style fingerprinting, feature engineering, and systematic validation against business metrics.
43
+
44
+ To learn more about fine-tuning competitively differentiated models, visit https://emulateframework.ai.
45
+ ## Intended Use
46
+ This model is designed for:
47
+ * Content creators seeking to generate professional LinkedIn posts
48
+ * Marketing professionals developing social media content
49
+ * Individuals looking to improve their LinkedIn presence with stylistically consistent posts
50
+ * Teams wanting to maintain brand voice across LinkedIn communications
51
+ ## Base Model: Qwen2.5-14B-Instruct
52
+ The fine-tuning builds upon Qwen2.5-14B-Instruct, which features:
53
+ * 14.7B parameters (13.1B non-embedding)
54
+ * Causal language model architecture with RoPE, SwiGLU, RMSNorm, and Attention QKV bias
55
+ * 48 layers with 40 attention heads for Q and 8 for KV
56
+ * Context length support up to 131,072 tokens with generation capability of 8,192 tokens
57
+ * Significant improvements in instruction following and generating structured outputs
58
+ ## Fine-tuning Dataset
59
+ The model was fine-tuned on a dataset of high-performing LinkedIn posts, analyzed for various writing style features including:
60
+ * Sentence structure patterns
61
+ * Vocabulary richness
62
+ * Line break usage
63
+ * Punctuation patterns
64
+ * Bullet styles
65
+ * Topic flow and shifts
66
+ * Narrative structure
67
+ * Pacing and sentiment arcs
68
+ ## Prompt Template
69
+ The model accepts stylized prompts in the following format:
70
+ ````
71
+ # Request
72
+ Create a LinkedIn post that **[structure type]** **on the topic of**: `[topic]`
73
+
74
+ ### Key Message
75
+ ```
76
+ [opinion] [context]
77
+ ```
78
+
79
+ ### Writing Constraints
80
+ - **Suggested Post Length**: [max_length]
81
+ - **Emoji Usage**: [emoji_usage]
82
+ - **Tone**: [tone]
83
+
84
+ ### Writing Style Features
85
+ - **Sentence Structure**: [sentence_structure_description]
86
+ - **Vocabulary Usage**: [vocabulary_usage_description]
87
+ - **Common Phrases**: [common_phrases_description]
88
+ - **Section Divider**: [divider_style]
89
+ - **Line Break Usage**: [line_break_description]
90
+ - **Punctuation**: [punctuation_description]
91
+ - **Bullet Styles**: [bullet_styles_description]
92
+ - **Topic Shifts**: [topic_shifts_description]
93
+ - **Narrative Flow**: [narrative_flow_description]
94
+ - **Pacing**: [pacing_description]
95
+ - **Sentiment Arc**: [sentiment_arc_description]
96
+ - **Profanity Level**: [profanity]
97
+ ````
98
+ # Parameters and Variables
99
+ ### Required Parameters
100
+ | Parameter | Type | Description | Possible Values |
101
+ |:-----------:|:----------:|:-----------------------------------:|:------------------------------------------------------------:|
102
+ | structure | String | Post structure type | "instructional", "reflective", "inspirational", "controversial", "insightful", "comparative", "announcement" |
103
+ | topic | Short text | Main subject of the post | Open-ended |
104
+ | opinion | Short text | The user's viewpoint | Open-ended |
105
+ | context | Long text | Background information for the post | Open-ended |
106
+ | max_length | String | Target length for the post | "Up to 750 characters long", "Between 750 and 1,500 characters long", "Between 1,500 and 3,000 characters long" |
107
+ | emoji_usage | String | Level of emoji inclusion | "none", "very low", "low", "medium", "high", "extreme" |
108
+ | tone | String | Overall emotional register | "adventurous", "artistic", "assertive", "authoritative", "bold", "bright", "calm", "capable", "caring", "casual", "charming", "cheerful", "clever", "cocky", "colorful", "comfortable", "conversational", "creative", "daring", "delightful", "detailed", "dramatic", "dry", "eccentric", "elegant", "endearing", "energetic", "engaging", "exciting", "fabulous", "fancy", "fierce", "formal", "friendly", "fun", "futuristic", "glamorous", "honorable", "industrial", "informative", "inspiring", "intense", "inviting", "lively", "natural", "no-nonsense", "persuasive", "playful", "powerful", "professional", "quirky", "rebellious", "reliable", "sarcastic", "savvy", "scholarly", "secure", "serious", "silly", "sleek", "smart", "soothing", "sophisticated", "stable", "stimulating", "strong", "swanky", "tasteful", "thoughtful", "trustworthy", "unconventional", "unique", "upbeat", "versatile", "whimsical", "witty" |
109
+ ### Optional Writing Style Features
110
+ | Feature | Type | Description |
111
+ |:-:|:-:|:-:|
112
+ | sentence_structure | Array | Lengths of sentences, analyzed for patterns and described |
113
+ | vocabulary_usage | Float | Ratio of unique words to total words, described in qualitative terms |
114
+ | common_phrases | Array | Distinctive phrases identified in the writing style |
115
+ | divider_style | String | Character pattern used to separate sections |
116
+ | line_breaks | Integer | Count of line breaks, with qualitative description |
117
+ | punctuation_usage | Object | Frequency of various punctuation marks |
118
+ | bullet_styles | String | Type of bullet point formatting |
119
+ | topic_shifts | Array | Indicators of subject changes throughout the post |
120
+ | flow | Array | Narrative progression patterns |
121
+ | pacing | String | Rhythm of the content delivery |
122
+ | sentiment_arc | String | Emotional progression pattern |
123
+ | profanity | String | Level of profanity allowed |
124
+ ## Style Feature Descriptions
125
+ ### Sentence Structure
126
+ Based on analysis of sentence lengths, classified as:
127
+ * "Short sentences, suggesting brevity and conciseness."
128
+ * "Long and complex sentences, indicating a detailed and elaborate style."
129
+ * "A mix of short and long sentences, showing a balanced style."
130
+ ### Vocabulary Usage
131
+ Calculated as a ratio of unique words to total words:
132
+ * 50% unique: "A rich vocabulary, showcasing extensive language use and depth."
133
+ * 35% unique: "A developed vocabulary, indicating a wide range of language and expression."
134
+ * 25% unique: "A normal vocabulary, reflecting a balanced and versatile use of language."
135
+ * 15% unique: "A conservative vocabulary, suggesting a focused and deliberate choice of words."
136
+ * ≤15% unique: "A very narrow vocabulary, highlighting a specific and targeted use of language."
137
+ ### Line Break Usage
138
+ Based on frequency and average density:
139
+ * No breaks: "No line breaks, indicating a continuous block of text."
140
+ * Many breaks: "Frequent line breaks, contributing to an easy-to-read structure."
141
+ * Few breaks: "Fewer line breaks, indicating a more compact writing style."
142
+ * Moderate: "A moderate number of line breaks, balancing readability and density."
143
+ ### Punctuation
144
+ Analysis of punctuation frequency relative to text length, with descriptions like:
145
+ * "Heavy use of periods/commas/exclamation marks/question marks/semicolons."
146
+ * "Regular use of periods/commas/exclamation marks/question marks/semicolons."
147
+ * "Standard punctuation usage."
148
+ ### Bullet Styles
149
+ Categorized as:
150
+ * Various symbol types: "-", "•", "#", "1.", "a.", etc.
151
+ * "Differing Emojis": Using various emojis as bullet points
152
+ * "EmojiBullets": Multiple emojis as bullets
153
+ * "Mixed Bullet Styles": Multiple formatting approaches
154
+ ### Topic Shifts
155
+ Based on semantic shift analysis between segments:
156
+ * Dynamic (>0.8): "Dynamic topic shifts, showing a highly versatile and engaging writing style."
157
+ * Regular (>0.6): "Regular topic shifts, reflecting a balanced and varied approach."
158
+ * Moderate (>0.4): "Moderate topic shifts, indicating a well-rounded but focused narrative."
159
+ * Conservative (>0.2): "Conservative topic shifts, suggesting a cautious approach to topic changes."
160
+ * Consistent (≤0.2): "Consistent topic focus, highlighting a deep and thorough exploration of subjects."
161
+ ### Narrative Flow
162
+ Captured as a sequence of content structure types:
163
+ * "Introduction/Setup"
164
+ * "Conflict/Resolution Point"
165
+ * "Introduction/Development"
166
+ * "Transition/Reflection"
167
+ ### Pacing
168
+ Classified as:
169
+ * "Fast"
170
+ * "Slow"
171
+ * "Variable"
172
+ * "Dynamic"
173
+ * "Moderate"
174
+ * "Short/Not Enough Data" (if <3 sentences)
175
+ ### Sentiment Arc
176
+ Progression of emotional tone:
177
+ * "Upward Trend": Increasingly positive
178
+ * "Downward Trend": Increasingly negative
179
+ * "Stable": Consistent emotional tone
180
+ * "Complex/Variable": Multiple shifts
181
+ * "Short/Not Enough Data for Arc": Insufficient for analysis
182
+ ## Limitations
183
+ * The model inherits the limitations of the base Qwen2.5-14B-Instruct model
184
+ * Style analysis is most accurate for English-language content
185
+ * Certain combinations of style parameters may produce inconsistent results
186
+ * Performance may vary for highly technical or specialized industry topics
187
+ * Not all writing style features may be represented in generated output with equal fidelity
188
+ ## Ethical Considerations
189
+ * The model should not be used to generate misleading or false professional information
190
+ * Users should verify factual claims in generated content before publishing on LinkedIn
191
+ * Consideration should be given to professional norms and cultural sensitivities in different industries and regions
192
+ ## Citation
193
+ ```
194
+ @misc{LinkedQwen2.5-14B-Instruct,
195
+ title = {LinkedQwen2.5-14B-Instruct: Fine-tuned LinkedIn Post Generator},
196
+ url = {https://huggingface.co/jacobpwarren/LinkedQwen2.5-14B-Instruct},
197
+ author = {Jacob Warren},
198
+ year = {2025},
199
+ month = {April}
200
+ }
201
+
202
+ @misc{qwen2.5,
203
+ title = {Qwen2.5: A Party of Foundation Models},
204
+ url = {https://qwenlm.github.io/blog/qwen2.5/},
205
+ author = {Qwen Team},
206
+ month = {September},
207
+ year = {2024}
208
+ }
209
  ```