diff options
| -rw-r--r-- | htroot/LLMSelection_p.html | 46 |
1 files changed, 28 insertions, 18 deletions
diff --git a/htroot/LLMSelection_p.html b/htroot/LLMSelection_p.html index baebcd342..74f38d48a 100644 --- a/htroot/LLMSelection_p.html +++ b/htroot/LLMSelection_p.html @@ -37,6 +37,10 @@ const PRODUCTION_MODEL_ACTION_COLUMN_INDEX = PRODUCTION_MODEL_TOTAL_COLUMNS - 1; const PRODUCTION_MODEL_TOOLING_COLUMN_INDEX = PRODUCTION_MODEL_FEATURE_COLUMN_START; const PRODUCTION_MODEL_VISION_COLUMN_INDEX = PRODUCTION_MODEL_FEATURE_COLUMN_START + 1; + const PRODUCTION_MODEL_ENABLED_USAGE_COLUMNS = new Set([ + 6, // chat + 11 // tldr + ]); const PRODUCTION_MODEL_COLUMN_NAMES = [ "service", "model", @@ -66,17 +70,20 @@ ["qwen2.5:1.5b-instruct-q4_K_M", " 0.88", "2GB", "Good small model for 1GB RAM", "Alibaba", "apache-2.0"], ["llama3.2:3b-instruct-q4_K_M", " 0.66", "3GB", "A good 3B model", "Meta", "llama3.2"], //["qwen3-vl:2b-instruct-q4_K_M", " 0.73", "3GB", "A very small vision-model, can understand what is sees in images"], - ["qwen3:4b-instruct-2507-q4_K_M", " 7.70", "3GB", "Exceptional good 4B model", "Alibaba", "apache-2.0"], ["hf.co/unsloth/medgemma-4b-it-GGUF:Q4_K_M", " 0.60", "4GB", "Medical Knowledge and Vision", "Google", "health-ai-developer-foundations"], ["olmo-3:7b-instruct-q4_K_M", " 2.22", "4GB", "open and accessible training data, open-source training code", "allenai.org", "apache-2.0"], - //["phi4:14b-q4_K_M", " 5.24", "10GB", "Strong, made with synthetic data", "Microsoft", "mit"], - ["hf.co/mradermacher/Ling-mini-2.0-GGUF:Q4_K_M", "20.00", "14GB", "very fast MoE model with 1.4B activated parameters per expert", "InclusionAI", "mit"], - //["magistral:24b-small-2506-q4_K_M", " 2.37", "16GB", "European flagship model, strong multilangual, reasoning", "mistral.ai", "apache-2.0"], - //["gemma3:27b-it-q4_K_M", " 4.81", "20GB", "Strong content safety, multilingual support in over 140 languages", "google.com", "gemma"], + ["qwen3:4b-instruct-2507-q4_K_M", " 7.70", "3GB", "a good 4B model", "Alibaba", "apache-2.0"], + ["hf.co/janhq/Jan-v3-4B-base-instruct-gguf:Q4_K_M", " 8.19", "6GB", "a brilliant 4B model, post-trained with large teacher from qwen3:4b", "jan.ai", "apache-2.0"], + ["ministral-3:14b-instruct-2512-q4_K_M", " 8.55", "10GB", "European flagship model, strong multilangual, vision, agentic", "mistral.ai", "apache-2.0"], + ["olmo-3.1:32b-instruct-q4_K_M", "10.25", "20GB", "open and accessible training data, open-source training code", "allenai.org", "apache-2.0"], + //["phi4:14b-q4_K_M", " 5.24", "10GB", "Strong, made with synthetic data", "Microsoft", "mit"], + //["gemma3:27b-it-q4_K_M", " 4.81", "20GB", "Strong content safety, multilingual support in over 140 languages", "google.com", "gemma"], //["qwen3-vl:30b-a3b-instruct-q4_K_M", "17.33", "22GB", "Very fast, exceptional good 30B model, ranking above GPT-4-turbo, GPT-4.1-nano, GPT-o1, GPT-4o-mini", "Alibaba", "apache-2.0"], - ["qwen3.5:35b-a3b-q4_K_M", "44.63", "25GB", "Very fast MoE, exceptional good 35B model with vision, ranking above GPT-4-turbo, GPT-4.1-nano, GPT-o1, GPT-4o-mini", "Alibaba", "apache-2.0"] + ["qwen3.5:9b-q4_K_M", "18.37", "14GB", "multimodal, outstanding for its size, long-context 256K Tokens, strong instruction following model", "Alibaba", "apache-2.0"], + ["hf.co/mradermacher/Ling-mini-2.0-GGUF:Q4_K_M", "20.00", "20GB", "very fast 16B MoE model with 1.4B activated parameters per expert", "InclusionAI", "mit"], + ["qwen3.5:35b-a3b-q4_K_M", "44.63", "25GB", "Very fast MoE, exceptional good 35B model with vision, ranking above GPT-4-turbo, GPT-4.1-nano, GPT-o1, GPT-4o-mini", "Alibaba", "apache-2.0"] ]; - + const MODEL_TABLE_HEADERS = ["Model", "Ranking", "Size", "Description", "Provider", "License", "Actions"]; const RECOMMENDED_MODEL_MAP = new Map( RECOMMENDED_MODELS.map(([name, ranking, size, description, provider, license]) => [ @@ -563,6 +570,10 @@ return button; } + function isSelectableUsageColumn(col) { + return PRODUCTION_MODEL_ENABLED_USAGE_COLUMNS.has(col); + } + function handleModelSelect(modelName) { if (!modelName) return; upsertProductionModel(modelName); @@ -668,18 +679,17 @@ checkbox.type = "checkbox"; cell.textContent = ""; cell.appendChild(checkbox); - checkbox.checked = !!defaultChecked && col <= PRODUCTION_MODEL_USAGE_COLUMN_END; - if (col >= PRODUCTION_MODEL_FEATURE_COLUMN_START) { - // disable the checkbox - checkbox.disabled = true - } + checkbox.checked = !!defaultChecked && isSelectableUsageColumn(col); } + checkbox.disabled = col >= PRODUCTION_MODEL_FEATURE_COLUMN_START || !isSelectableUsageColumn(col); + if (!isSelectableUsageColumn(col)) checkbox.checked = false; initializeUsageCheckbox(checkbox, col); } if (defaultChecked) { // enforce feature exclusivity for row if (!row) return; for (let col = PRODUCTION_MODEL_USAGE_COLUMN_START; col <= PRODUCTION_MODEL_USAGE_COLUMN_END; col += 1) { + if (!isSelectableUsageColumn(col)) continue; const cell = row.cells[col]; if (!cell) continue; const checkbox = cell.querySelector('input[type="checkbox"]'); @@ -804,7 +814,7 @@ PRODUCTION_MODEL_COLUMN_NAMES.forEach((columnName, index) => { if (index >= PRODUCTION_MODEL_USAGE_COLUMN_START && index <= PRODUCTION_MODEL_FEATURE_COLUMN_END) { const checkbox = row.cells[index] ? row.cells[index].querySelector('input[type="checkbox"]') : null; - rowData[columnName] = checkbox ? checkbox.checked : false; + rowData[columnName] = checkbox && (index >= PRODUCTION_MODEL_FEATURE_COLUMN_START || isSelectableUsageColumn(index)) ? checkbox.checked : false; } else { rowData[columnName] = row.cells[index] ? row.cells[index].textContent.trim() : ""; } @@ -1285,12 +1295,12 @@ <td>#[api_key]#</td> <td>#[max_tokens]#</td> - <td><input type="checkbox" #(search)#::checked=true#(/search)#></td> + <td><input type="checkbox" #(search)#::checked=true#(/search)# disabled="disabled"></td> <td><input type="checkbox" #(chat)#::checked=true#(/chat)#></td> - <td><input type="checkbox" #(translation)#::checked=true#(/translation)#></td> - <td><input type="checkbox" #(classification)#::checked=true#(/classification)#></td> - <td><input type="checkbox" #(query)#::checked=true#(/query)#></td> - <td><input type="checkbox" #(qapairs)#::checked=true#(/qapairs)#></td> + <td><input type="checkbox" #(translation)#::checked=true#(/translation)# disabled="disabled"></td> + <td><input type="checkbox" #(classification)#::checked=true#(/classification)# disabled="disabled"></td> + <td><input type="checkbox" #(query)#::checked=true#(/query)# disabled="disabled"></td> + <td><input type="checkbox" #(qapairs)#::checked=true#(/qapairs)# disabled="disabled"></td> <td><input type="checkbox" #(tldr)#::checked=true#(/tldr)#></td> <td><input type="checkbox" #(tooling)#::checked=true#(/tooling)# disabled=true></td> |