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nexsendev
/
webicoder-v3-mlx-q4

Text Generation
MLX
Safetensors
English
phi
phi-2
html
css
web-development
code-generation
fine-tuned
apple-silicon
conversational
4-bit precision
Model card Files
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  1. ._.cache +0 -0
  2. .cache/._huggingface +0 -0
  3. .gitattributes +1 -0
  4. LICENSE +21 -0
  5. README.md +307 -0
  6. added_tokens.json +40 -0
  7. config.json +43 -0
  8. example.py +198 -0
  9. generation_config.json +18 -0
  10. merges.txt +0 -0
  11. model.safetensors +3 -0
  12. model.safetensors.index.json +849 -0
  13. special_tokens_map.json +23 -0
  14. tokenizer.json +0 -0
  15. tokenizer_config.json +328 -0
  16. vocab.json +0 -0
  17. webicoder_icon.png +3 -0
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.cache/._huggingface ADDED
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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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  *.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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+ webicoder_icon.png filter=lfs diff=lfs merge=lfs -text
LICENSE ADDED
@@ -0,0 +1,21 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ MIT License
2
+
3
+ Copyright (c) 2025 WebICoder
4
+
5
+ Permission is hereby granted, free of charge, to any person obtaining a copy
6
+ of this software and associated documentation files (the "Software"), to deal
7
+ in the Software without restriction, including without limitation the rights
8
+ to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
9
+ copies of the Software, and to permit persons to whom the Software is
10
+ furnished to do so, subject to the following conditions:
11
+
12
+ The above copyright notice and this permission notice shall be included in all
13
+ copies or substantial portions of the Software.
14
+
15
+ THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
16
+ IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
17
+ FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
18
+ AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
19
+ LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
20
+ OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
21
+ SOFTWARE.
README.md ADDED
@@ -0,0 +1,307 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: mit
3
+ language:
4
+ - en
5
+ tags:
6
+ - mlx
7
+ - phi-2
8
+ - html
9
+ - css
10
+ - web-development
11
+ - code-generation
12
+ - fine-tuned
13
+ - apple-silicon
14
+ base_model: microsoft/phi-2
15
+ pipeline_tag: text-generation
16
+ library_name: mlx
17
+ model-index:
18
+ - name: WebICoder-v3-MLX-4bit
19
+ results: []
20
+ ---
21
+
22
+ # ⚡ WebICoder v3 — HTML Code Generation (MLX 4-bit)
23
+
24
+ **WebICoder v3** is a fine-tuned version of [Microsoft Phi-2](https://huggingface.co/microsoft/phi-2) (2.7B parameters) specialized in generating **complete, production-ready HTML/CSS websites** from natural language descriptions.
25
+
26
+ Optimized for **Apple Silicon** via [MLX](https://github.com/ml-explore/mlx).
27
+
28
+ ## Model Details
29
+
30
+ | Property | Value |
31
+ |---|---|
32
+ | **Base Model** | Microsoft Phi-2 (2.7B parameters) |
33
+ | **Architecture** | PhiForCausalLM (32 layers, 2560 hidden) |
34
+ | **Format** | MLX (Apple Silicon optimized) |
35
+ | **Quantization** | 4-bit (4.504 bits/weight, affine) |
36
+ | **Size** | ~1.5 GB |
37
+ | **Context Length** | 4096 tokens |
38
+ | **Task** | HTML/CSS Code Generation |
39
+ | **Speed** | ~20-40 tok/s on M-series Mac |
40
+
41
+ ## Also Available
42
+
43
+ | Variant | Link | Size |
44
+ |---|---|---|
45
+ | **8-bit** (higher quality) | `YOUR_USERNAME/WebICoder-v3-MLX-8bit` | ~2.9 GB |
46
+
47
+ ---
48
+
49
+ ## ⚠️ MANDATORY — Read Before Using
50
+
51
+ > **If you skip these steps, the model will produce broken, repeated, or low-quality output.**
52
+ > Follow ALL 5 rules below to get the best results.
53
+
54
+ ### Rule 1 — Use the correct prompt format
55
+
56
+ The model was trained with an **Alpaca-style format**. You MUST wrap your prompt like this:
57
+
58
+ ```
59
+ ### Instruction:
60
+ {your website description here}
61
+
62
+ ### Response:
63
+ ```
64
+
65
+ ❌ **DO NOT** send raw text like `"Create a website"` — the model won't understand it correctly.
66
+
67
+ ✅ **DO** use the format above, or use `tokenizer.apply_chat_template()` which does it automatically.
68
+
69
+ ### Rule 2 — ALWAYS stop at `</html>`
70
+
71
+ The model does not always emit an EOS token after finishing the HTML. You **MUST** check for `</html>` in the output and stop generation when you see it.
72
+
73
+ ```python
74
+ # ✅ Correct — stop at </html>
75
+ for response in stream_generate(model, tokenizer, prompt=prompt, max_tokens=4096, sampler=sampler):
76
+ full_text += response.text
77
+ if "</html>" in full_text:
78
+ break
79
+ ```
80
+
81
+ ❌ Without this, the model will **repeat the entire page** in a loop.
82
+
83
+ ### Rule 3 — Use repetition penalty
84
+
85
+ A repetition penalty is **essential** to prevent the model from generating duplicate sections (e.g., the same footer twice, identical testimonials).
86
+
87
+ ```python
88
+ from mlx_lm.sample_utils import make_logits_processors
89
+
90
+ logits_processors = make_logits_processors(repetition_penalty=1.2, repetition_context_size=256)
91
+ ```
92
+
93
+ Then pass `logits_processors=logits_processors` to `stream_generate()`.
94
+
95
+ ### Rule 4 — Use low temperature (0.3 – 0.5)
96
+
97
+ High temperature (> 0.7) produces incoherent, broken HTML. **Always use 0.3 – 0.5**.
98
+
99
+ ```python
100
+ from mlx_lm.sample_utils import make_sampler
101
+
102
+ sampler = make_sampler(temp=0.4) # ✅ Recommended
103
+ ```
104
+
105
+ ### Rule 5 — Post-process the output
106
+
107
+ The model may occasionally prepend training artifacts (system prompt) before the HTML. **Always clean the output:**
108
+
109
+ ```python
110
+ import re
111
+
112
+ def clean_html(text: str) -> str:
113
+ """Extract clean HTML from model output."""
114
+ # Remove leaked system prompts
115
+ text = re.sub(r"You are (?:Deep|Web[iI])coder.*?production-ready code\.\n*", "", text, flags=re.DOTALL)
116
+ text = re.sub(r"### Instruction:.*", "", text, flags=re.DOTALL)
117
+ text = re.sub(r"### Response:\s*", "", text, flags=re.DOTALL)
118
+
119
+ # Extract HTML document
120
+ match = re.search(r"(<(?:!DOCTYPE\s+html|html)[\s\S]*?</html>)", text, re.IGNORECASE)
121
+ if match:
122
+ return match.group(1).strip()
123
+
124
+ # Fallback
125
+ start = re.search(r"<(?:!DOCTYPE|html|head|body)", text, re.IGNORECASE)
126
+ if start:
127
+ html = text[start.start():].strip()
128
+ if not html.lower().startswith("<!doctype"):
129
+ html = "<!DOCTYPE html>\n<html>\n" + html + "\n</html>"
130
+ return html
131
+
132
+ return text.strip()
133
+ ```
134
+
135
+ ---
136
+
137
+ ## Quick Start — Complete Working Example
138
+
139
+ Copy-paste this and it will work:
140
+
141
+ ```python
142
+ from mlx_lm import load, stream_generate
143
+ from mlx_lm.sample_utils import make_sampler, make_logits_processors
144
+ import re
145
+
146
+ # 1. Load model
147
+ model, tokenizer = load("YOUR_USERNAME/WebICoder-v3-MLX-4bit")
148
+
149
+ # 2. Format prompt (MANDATORY)
150
+ user_prompt = "Create a modern portfolio website with a hero, project cards, and a contact form"
151
+
152
+ prompt = f"""### Instruction:
153
+ {user_prompt}
154
+
155
+ ### Response:
156
+ """
157
+
158
+ # 3. Configure sampler + repetition penalty (MANDATORY)
159
+ sampler = make_sampler(temp=0.4)
160
+ logits_processors = make_logits_processors(repetition_penalty=1.2, repetition_context_size=256)
161
+
162
+ # 4. Generate with stop at </html> (MANDATORY)
163
+ full_text = ""
164
+ for response in stream_generate(
165
+ model, tokenizer,
166
+ prompt=prompt,
167
+ max_tokens=4096,
168
+ sampler=sampler,
169
+ logits_processors=logits_processors,
170
+ ):
171
+ full_text += response.text
172
+ print(response.text, end="", flush=True)
173
+
174
+ if "</html>" in full_text or response.finish_reason:
175
+ break
176
+
177
+ # 5. Clean output (MANDATORY)
178
+ def clean_html(text):
179
+ text = re.sub(r"You are (?:Deep|Web[iI])coder.*?production-ready code\.\n*", "", text, flags=re.DOTALL)
180
+ match = re.search(r"(<(?:!DOCTYPE\s+html|html)[\s\S]*?</html>)", text, re.IGNORECASE)
181
+ return match.group(1).strip() if match else text.strip()
182
+
183
+ html = clean_html(full_text)
184
+
185
+ # Save to file
186
+ with open("output.html", "w") as f:
187
+ f.write(html)
188
+ print(f"\n\nSaved to output.html ({len(html)} chars)")
189
+ ```
190
+
191
+ ---
192
+
193
+ ## Recommended Parameters Summary
194
+
195
+ | Parameter | Value | Mandatory? |
196
+ |---|---|:---:|
197
+ | **Prompt format** | `### Instruction:` / `### Response:` | ✅ YES |
198
+ | **Temperature** | 0.3 – 0.5 | ✅ YES |
199
+ | **Repetition Penalty** | 1.2 | ✅ YES |
200
+ | **Repetition Context** | 256 | ✅ YES |
201
+ | **Max Tokens** | 4096 | ✅ YES |
202
+ | **Stop at `</html>`** | Check output and break | ✅ YES |
203
+ | **Post-processing** | `clean_html()` function | ✅ YES |
204
+ | **Top-p** | 0.9 | Recommended |
205
+ | **Top-k** | 50 | Optional |
206
+
207
+ ---
208
+
209
+ ## Using the Chat Template
210
+
211
+ The tokenizer includes a built-in chat template that handles prompt formatting automatically:
212
+
213
+ ```python
214
+ messages = [
215
+ {"role": "user", "content": "Create a dark-themed portfolio website with project cards"}
216
+ ]
217
+
218
+ prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
219
+ # This automatically wraps it in ### Instruction: / ### Response: format
220
+ ```
221
+
222
+ ## Using the Example Script
223
+
224
+ ```bash
225
+ # Single prompt
226
+ python example.py "Create a landing page for a coffee shop"
227
+
228
+ # Interactive mode
229
+ python example.py --interactive
230
+ ```
231
+
232
+ ---
233
+
234
+ ## Example Outputs
235
+
236
+ | Prompt | What You Get |
237
+ |---|---|
238
+ | "Create a portfolio with a hero and project cards" | Nav, animated hero, glassmorphism cards, contact form, footer |
239
+ | "Create a landing page for a fitness app" | Hero gradient, feature cards, testimonials, CTA, footer |
240
+ | "Create a pricing page with 3 tiers" | Toggle monthly/yearly, feature lists, highlighted plan |
241
+ | "Create a login page with split layout" | Gradient left, form right, social login buttons |
242
+
243
+ ---
244
+
245
+ ## What the Model Generates
246
+
247
+ When properly configured, WebICoder v3 produces:
248
+
249
+ - ✅ Complete `<!DOCTYPE html>` with `<head>`, `<meta>`, `<title>`
250
+ - ✅ **Vanilla CSS** — custom properties, gradients, glassmorphism, `backdrop-filter`
251
+ - ✅ **Responsive design** — `@media` queries, `clamp()`, CSS Grid `auto-fit`
252
+ - ✅ **Animations** — `fade-in` with `IntersectionObserver`, hover transitions
253
+ - ✅ **Modern design** — gradient text, blur effects, rounded corners, shadows
254
+ - ✅ **Complete pages** — nav, hero, content sections, footer
255
+
256
+ ---
257
+
258
+ ## Limitations
259
+
260
+ - Optimized for **single-page HTML** with embedded CSS/JS
261
+ - Context window: **4096 tokens** — very complex multi-section pages may still be truncated
262
+ - Based on Phi-2 (2.7B) — larger models will produce more sophisticated output
263
+ - English prompts work best
264
+
265
+ ---
266
+
267
+ ## Training Details
268
+
269
+ | Property | Value |
270
+ |---|---|
271
+ | **Base Model** | microsoft/phi-2 |
272
+ | **Fine-tuning** | Full fine-tuning on HTML/CSS code pairs |
273
+ | **Training Format** | Alpaca-style (Instruction / Response) |
274
+ | **Training Context** | 4096 tokens |
275
+ | **Precision** | float16 |
276
+ | **Quantization** | Post-training 4-bit (MLX affine, group_size=64) |
277
+
278
+ ---
279
+
280
+ ## Files Included
281
+
282
+ | File | Description |
283
+ |---|---|
284
+ | `model.safetensors` | Quantized model weights |
285
+ | `config.json` | Model architecture configuration |
286
+ | `tokenizer.json` | Tokenizer vocabulary |
287
+ | `tokenizer_config.json` | Tokenizer settings with chat template |
288
+ | `generation_config.json` | Recommended generation parameters |
289
+ | `example.py` | Ready-to-use example script with all mandatory rules |
290
+ | `LICENSE` | MIT License |
291
+
292
+ ---
293
+
294
+ ## Citation
295
+
296
+ ```bibtex
297
+ @misc{webicoder-v3,
298
+ title={WebICoder v3: Fine-tuned Phi-2 for HTML Code Generation},
299
+ year={2025},
300
+ publisher={Hugging Face},
301
+ url={https://huggingface.co/YOUR_USERNAME/WebICoder-v3-MLX-4bit}
302
+ }
303
+ ```
304
+
305
+ ## License
306
+
307
+ MIT License — see [LICENSE](LICENSE) for details.
added_tokens.json ADDED
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+ {
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+ "\t\t": 50294,
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+ "\t\t\t": 50293,
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+ "\t\t\t\t": 50292,
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+ "\t\t\t\t\t": 50291,
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+ "\t\t\t\t\t\t": 50290,
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+ "\t\t\t\t\t\t\t": 50289,
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+ "\t\t\t\t\t\t\t\t": 50288,
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+ "\t\t\t\t\t\t\t\t\t": 50287,
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+ " ": 50286,
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+ " ": 50285,
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+ " ": 50284,
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+ " ": 50283,
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+ " ": 50282,
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+ " ": 50281,
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+ " ": 50280,
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+ " ": 50279,
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+ " ": 50278,
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+ " ": 50277,
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+ " ": 50276,
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+ " ": 50275,
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+ " ": 50274,
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+ " ": 50273,
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+ " ": 50272,
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+ " ": 50271,
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+ " ": 50270,
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+ " ": 50269,
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+ " ": 50268,
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+ " ": 50267,
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+ " ": 50266,
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+ " ": 50265,
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+ " ": 50264,
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+ " ": 50263,
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+ " ": 50262,
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+ " ": 50261,
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+ " ": 50260,
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+ " ": 50259,
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+ " ": 50258,
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+ " ": 50257
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+ }
config.json ADDED
@@ -0,0 +1,43 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "architectures": [
3
+ "PhiForCausalLM"
4
+ ],
5
+ "attention_dropout": 0.0,
6
+ "bos_token_id": 50256,
7
+ "dtype": "float16",
8
+ "embd_pdrop": 0.0,
9
+ "eos_token_id": 50256,
10
+ "hidden_act": "gelu_new",
11
+ "hidden_size": 2560,
12
+ "initializer_range": 0.02,
13
+ "intermediate_size": 10240,
14
+ "layer_norm_eps": 1e-05,
15
+ "max_position_embeddings": 4096,
16
+ "model_type": "phi",
17
+ "num_attention_heads": 32,
18
+ "num_hidden_layers": 32,
19
+ "num_key_value_heads": 32,
20
+ "pad_token_id": 50256,
21
+ "partial_rotary_factor": 0.4,
22
+ "qk_layernorm": false,
23
+ "quantization": {
24
+ "group_size": 64,
25
+ "bits": 4,
26
+ "mode": "affine"
27
+ },
28
+ "quantization_config": {
29
+ "group_size": 64,
30
+ "bits": 4,
31
+ "mode": "affine"
32
+ },
33
+ "resid_pdrop": 0.1,
34
+ "rope_parameters": {
35
+ "partial_rotary_factor": 0.4,
36
+ "rope_theta": 10000.0,
37
+ "rope_type": "default"
38
+ },
39
+ "tie_word_embeddings": false,
40
+ "transformers_version": "5.0.0",
41
+ "use_cache": true,
42
+ "vocab_size": 51200
43
+ }
example.py ADDED
@@ -0,0 +1,198 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ #!/usr/bin/env python3
2
+ """
3
+ WebICoder v3 — Quick Start Example
4
+ Generate HTML websites from natural language prompts using MLX on Apple Silicon.
5
+
6
+ ⚠️ MANDATORY: This script implements all 5 required rules for correct output.
7
+ See README.md for full documentation.
8
+
9
+ Usage:
10
+ python example.py "Create a landing page for a coffee shop"
11
+ python example.py --interactive
12
+ """
13
+
14
+ import sys
15
+ import re
16
+
17
+ from mlx_lm import load, stream_generate
18
+ from mlx_lm.sample_utils import make_sampler, make_logits_processors
19
+
20
+
21
+ # ─── Configuration ──────────────────────────────────────────────────────────
22
+ MODEL_PATH = "." # Current directory (the model repo)
23
+
24
+ # RULE 1: System prompt + Alpaca format (### Instruction / ### Response)
25
+ SYSTEM_PROMPT = (
26
+ "You are WebICoder, an expert frontend web developer specializing in premium, "
27
+ "Apple-inspired design. You create stunning websites using only HTML, CSS, and "
28
+ "vanilla JavaScript. Your designs feature: minimalist layouts, elegant typography, "
29
+ "smooth animations, glassmorphism effects, generous whitespace, and a refined "
30
+ "color palette. You always produce complete, production-ready code."
31
+ )
32
+
33
+ # RULE 2: Stop sequences — MANDATORY to prevent infinite loops
34
+ STOP_SEQUENCES = ["</html>", "### Instruction:", "You are Deepcoder", "You are WebICoder"]
35
+
36
+ # RULE 4: Low temperature — MANDATORY for coherent HTML
37
+ DEFAULT_TEMP = 0.4
38
+ DEFAULT_MAX_TOKENS = 4096
39
+
40
+
41
+ # ─── RULE 1: Prompt Formatting (MANDATORY) ──────────────────────────────────
42
+
43
+ def format_prompt(user_input: str) -> str:
44
+ """
45
+ MANDATORY: Format user input into the model's training prompt format.
46
+
47
+ The model was trained with Alpaca-style prompts. Sending raw text
48
+ without this formatting will produce garbage output.
49
+ """
50
+ return f"{SYSTEM_PROMPT}\n\n### Instruction:\n{user_input}\n\n### Response:\n"
51
+
52
+
53
+ # ─── RULE 5: Post-Processing (MANDATORY) ────────────────────────────────────
54
+
55
+ def clean_html(text: str) -> str:
56
+ """
57
+ MANDATORY: Extract clean HTML from model output.
58
+
59
+ The model may leak training artifacts (system prompt, instruction markers).
60
+ This function strips them and returns only valid HTML.
61
+ """
62
+ # Remove system prompt leaks
63
+ for pattern in [
64
+ r"You are (?:Deep|Web[iI])coder.*?production-ready code\.\n*",
65
+ r"### Instruction:.*",
66
+ r"### Response:\s*",
67
+ ]:
68
+ text = re.sub(pattern, "", text, flags=re.DOTALL)
69
+
70
+ # Extract complete HTML document
71
+ html_match = re.search(r"(<(?:!DOCTYPE\s+html|html)[\s\S]*?</html>)", text, re.IGNORECASE)
72
+ if html_match:
73
+ return html_match.group(1).strip()
74
+
75
+ # Fallback: find any HTML content and wrap it
76
+ html_start = re.search(r"<(?:!DOCTYPE|html|head|body|link)", text, re.IGNORECASE)
77
+ if html_start:
78
+ html = text[html_start.start():].strip()
79
+ if not html.lower().startswith("<!doctype"):
80
+ html = "<!DOCTYPE html>\n<html>\n" + html
81
+ if "</html>" not in html.lower():
82
+ html += "\n</html>"
83
+ return html
84
+
85
+ return text.strip()
86
+
87
+
88
+ # ─── Generation ─────────────────────────────────────────────────────────────
89
+
90
+ def generate_html(prompt: str, temperature: float = DEFAULT_TEMP, max_tokens: int = DEFAULT_MAX_TOKENS) -> str:
91
+ """
92
+ Generate HTML from a natural language prompt.
93
+
94
+ Implements all 5 mandatory rules:
95
+ 1. Prompt formatting (### Instruction / ### Response)
96
+ 2. Stop at </html>
97
+ 3. Repetition penalty (1.2, context=256)
98
+ 4. Low temperature (0.4)
99
+ 5. Post-processing (clean_html)
100
+ """
101
+ print(f"[INFO] Loading model from: {MODEL_PATH}")
102
+ model, tokenizer = load(MODEL_PATH)
103
+
104
+ # RULE 1: Format the prompt
105
+ formatted_prompt = format_prompt(prompt)
106
+
107
+ # RULE 4: Low temperature sampler
108
+ sampler = make_sampler(temp=temperature)
109
+
110
+ # RULE 3: Repetition penalty — MANDATORY
111
+ logits_processors = make_logits_processors(
112
+ repetition_penalty=1.2,
113
+ repetition_context_size=256,
114
+ )
115
+
116
+ print(f"[INFO] Generating (temp={temperature}, max_tokens={max_tokens}, rep_penalty=1.2)...")
117
+ print("─" * 60)
118
+
119
+ full_text = ""
120
+ last_response = None
121
+
122
+ for response in stream_generate(
123
+ model, tokenizer,
124
+ prompt=formatted_prompt,
125
+ max_tokens=max_tokens,
126
+ sampler=sampler,
127
+ logits_processors=logits_processors, # RULE 3
128
+ ):
129
+ last_response = response
130
+ token_str = response.text
131
+ full_text += token_str
132
+ print(token_str, end="", flush=True)
133
+
134
+ # RULE 2: Stop at </html> — MANDATORY
135
+ should_stop = False
136
+ for stop_seq in STOP_SEQUENCES:
137
+ if stop_seq in full_text:
138
+ idx = full_text.find(stop_seq)
139
+ if stop_seq == "</html>":
140
+ full_text = full_text[:idx + len(stop_seq)]
141
+ else:
142
+ full_text = full_text[:idx]
143
+ should_stop = True
144
+ break
145
+
146
+ if should_stop or response.finish_reason is not None:
147
+ break
148
+
149
+ print("\n" + "─" * 60)
150
+ if last_response:
151
+ print(f"[INFO] Generated {last_response.generation_tokens} tokens at {last_response.generation_tps:.1f} tok/s")
152
+ print(f"[INFO] Peak memory: {last_response.peak_memory:.2f} GB")
153
+
154
+ # RULE 5: Clean the output — MANDATORY
155
+ return clean_html(full_text)
156
+
157
+
158
+ # ─── Main ────────────────────────────────────────────────────────────────────
159
+
160
+ def main():
161
+ if len(sys.argv) > 1 and sys.argv[1] != "--interactive":
162
+ # Single prompt mode
163
+ prompt = " ".join(sys.argv[1:])
164
+ html = generate_html(prompt)
165
+
166
+ output_file = "output.html"
167
+ with open(output_file, "w") as f:
168
+ f.write(html)
169
+ print(f"\n[INFO] Saved to {output_file} ({len(html)} chars)")
170
+
171
+ else:
172
+ # Interactive mode
173
+ print("=" * 60)
174
+ print(" ⚡ WebICoder v3 — Interactive Mode")
175
+ print(" Type a website description, press Enter to generate.")
176
+ print(" Type 'quit' to exit.")
177
+ print("=" * 60)
178
+
179
+ while True:
180
+ try:
181
+ prompt = input("\n🌐 Describe your website: ").strip()
182
+ if not prompt or prompt.lower() in ("quit", "exit", "q"):
183
+ break
184
+
185
+ html = generate_html(prompt)
186
+
187
+ output_file = "output.html"
188
+ with open(output_file, "w") as f:
189
+ f.write(html)
190
+ print(f"\n[INFO] Saved to {output_file} ({len(html)} chars)")
191
+
192
+ except KeyboardInterrupt:
193
+ print("\n[INFO] Bye!")
194
+ break
195
+
196
+
197
+ if __name__ == "__main__":
198
+ main()
generation_config.json ADDED
@@ -0,0 +1,18 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ {
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+ "_from_model_config": true,
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+ "bos_token_id": 50256,
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+ "do_sample": true,
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+ "temperature": 0.4,
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+ "top_p": 0.9,
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+ "top_k": 50,
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+ "repetition_penalty": 1.15,
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+ "max_new_tokens": 4096,
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+ "stop_strings": [
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+ "</html>",
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+ "### Instruction:",
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+ "You are Deepcoder",
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+ "You are WebICoder"
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+ ],
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+ "transformers_version": "5.0.0"
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+ }
merges.txt ADDED
The diff for this file is too large to render. See raw diff
 
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256
+ "rstrip": false,
257
+ "single_word": false,
258
+ "special": false
259
+ },
260
+ "50288": {
261
+ "content": "\t\t\t\t\t\t\t\t",
262
+ "lstrip": false,
263
+ "normalized": true,
264
+ "rstrip": false,
265
+ "single_word": false,
266
+ "special": false
267
+ },
268
+ "50289": {
269
+ "content": "\t\t\t\t\t\t\t",
270
+ "lstrip": false,
271
+ "normalized": true,
272
+ "rstrip": false,
273
+ "single_word": false,
274
+ "special": false
275
+ },
276
+ "50290": {
277
+ "content": "\t\t\t\t\t\t",
278
+ "lstrip": false,
279
+ "normalized": true,
280
+ "rstrip": false,
281
+ "single_word": false,
282
+ "special": false
283
+ },
284
+ "50291": {
285
+ "content": "\t\t\t\t\t",
286
+ "lstrip": false,
287
+ "normalized": true,
288
+ "rstrip": false,
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+ "single_word": false,
290
+ "special": false
291
+ },
292
+ "50292": {
293
+ "content": "\t\t\t\t",
294
+ "lstrip": false,
295
+ "normalized": true,
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+ "rstrip": false,
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+ "single_word": false,
298
+ "special": false
299
+ },
300
+ "50293": {
301
+ "content": "\t\t\t",
302
+ "lstrip": false,
303
+ "normalized": true,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": false
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+ },
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+ "50294": {
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+ "content": "\t\t",
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+ "lstrip": false,
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+ "normalized": true,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": false
315
+ }
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+ },
317
+ "backend": "tokenizers",
318
+ "bos_token": "<|endoftext|>",
319
+ "clean_up_tokenization_spaces": true,
320
+ "eos_token": "<|endoftext|>",
321
+ "extra_special_tokens": {},
322
+ "is_local": false,
323
+ "model_max_length": 4096,
324
+ "return_token_type_ids": false,
325
+ "tokenizer_class": "CodeGenTokenizer",
326
+ "unk_token": "<|endoftext|>",
327
+ "chat_template": "{% for message in messages %}{% if message['role'] == 'system' %}{{ message['content'] + '\n' }}{% elif message['role'] == 'user' %}### Instruction:\n{{ message['content'] }}\n\n### Response:\n{% elif message['role'] == 'assistant' %}{{ message['content'] }}{% endif %}{% endfor %}{% if add_generation_prompt %}### Response:\n{% endif %}"
328
+ }
vocab.json ADDED
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webicoder_icon.png ADDED

Git LFS Details

  • SHA256: 343a0976e565c05162129f1fb612f2a996156ec722b7fd824cba4560c6b2a02b
  • Pointer size: 131 Bytes
  • Size of remote file: 318 kB