Merge pull request #1144 from transformerlab/update/torch-291

Update torch to 2.9.1 and add some fixes

Author: deep1401

api/pyproject.toml

@@ -46,9 +46,9 @@ dependencies = [
 [project.optional-dependencies]
 nvidia = [
   # NVIDIA-specific packages
-  "torch==2.8.0",
-  "torchaudio==2.8.0",
-  "torchvision==0.23.0",
+  "torch==2.9.1",
+  "torchaudio==2.9.1",
+  "torchvision==0.24.1",
   "nvidia-ml-py==12.575.51",
   # Packages with versions (using no-gpu/nvidia versions)
   "accelerate==1.3.0",
@@ -68,9 +68,9 @@ nvidia = [
 ]
 rocm = [
   # ROCm-specific packages
-  "torch==2.8.0+rocm6.4",
-  "torchaudio==2.8.0+rocm6.4",
-  "torchvision==0.23.0+rocm6.4",
+  "torch==2.9.1+rocm6.4",
+  "torchaudio==2.9.1+rocm6.4",
+  "torchvision==0.24.1+rocm6.4",
   "pyrsmi==0.2.0",
   # Packages with ROCm-specific versions
   "accelerate==1.6.0",
@@ -90,9 +90,9 @@ rocm = [
 ]
 cpu = [
   # CPU-specific packages
-  "torch==2.8.0",
-  "torchaudio==2.8.0",
-  "torchvision==0.23.0",
+  "torch==2.9.1",
+  "torchaudio==2.9.1",
+  "torchvision==0.24.1",
   # Packages with versions (using no-gpu/cpu versions)
   "accelerate==1.3.0",
   "aiosqlite==0.20.0",

api/transformerlab/plugins/airllm_mlx_server/index.json

@@ -4,7 +4,7 @@
   "description": "Performing inference using AirLLM on your Apple Silicon machine",
   "plugin-format": "python",
   "type": "loader",
-  "version": "0.1.7",
+  "version": "0.1.8",
   "model_architectures": [
     "MLX",
     "CohereForCausalLM",
@@ -20,13 +20,8 @@
     "Phi3ForCausalLM",
     "Qwen2ForCausalLM"
   ],
-  "supported_hardware_architectures": [
-    "mlx"
-  ],
-  "files": [
-    "main.py",
-    "setup.sh"
-  ],
+  "supported_hardware_architectures": ["mlx"],
+  "files": ["main.py", "setup.sh"],
   "setup-script": "setup.sh",
   "parameters": {}
 }

api/transformerlab/plugins/autotrain_sft_trainer/index.json

@@ -4,7 +4,7 @@
   "description": "SFT training using Huggingface autotrain",
   "plugin-format": "python",
   "type": "trainer",
-  "version": "0.1.14",
+  "version": "0.1.15",
   "model_architectures": [
     "LlamaForCausalLM",
     "MistralForCausalLM",
@@ -17,11 +17,7 @@
     "Phi3ForCausalLM"
   ],
   "supported_hardware_architectures": [],
-  "files": [
-    "main.py",
-    "info.md",
-    "setup.sh"
-  ],
+  "files": ["main.py", "info.md", "setup.sh"],
   "setup-script": "setup.sh",
   "parameters": {
     "batch_size": {
@@ -34,7 +30,7 @@
       "title": "Learning Rate",
       "type": "number",
       "default": 0.0002,
-      "minimum": 1e-06
+      "minimum": 1e-6
     },
     "num_train_epochs": {
       "title": "Number of Training Epochs",

api/transformerlab/plugins/basic_evals/index.json

@@ -5,19 +5,11 @@
   "description": "Evaluating outputs of LLMs using basic defined metrics",
   "plugin-format": "python",
   "type": "evaluator",
-  "version": "0.1.8",
+  "version": "0.1.9",
   "git": "",
   "url": "",
-  "files": [
-    "main.py",
-    "setup.sh"
-  ],
-  "supported_hardware_architectures": [
-    "cpu",
-    "cuda",
-    "mlx",
-    "amd"
-  ],
+  "files": ["main.py", "setup.sh"],
+  "supported_hardware_architectures": ["cpu", "cuda", "mlx", "amd"],
   "_dataset": true,
   "_dataset_display_message": "Please make sure the name of the input and output columns match the ones in your dataset",
   "setup-script": "setup.sh",
@@ -66,22 +58,14 @@
           "return_type": {
             "type": "string",
             "title": "Output Type",
-            "enum": [
-              "boolean",
-              "number",
-              "contains",
-              "isequal",
-              "code"
-            ]
+            "enum": ["boolean", "number", "contains", "isequal", "code"]
           }
         }
       }
     },
     "limit": {
       "title": "Fraction of samples to evaluate",
-      "type": [
-        "number"
-      ],
+      "type": ["number"],
       "minimum": 0.0,
       "default": 1.0,
       "maximum": 1.0,

api/transformerlab/plugins/batched_generation_datasets/index.json

@@ -4,18 +4,11 @@
   "description": "Use a local or commercial LLM to generated outputs for the dataset generated.",
   "plugin-format": "python",
   "type": "generator",
-  "version": "0.1.11",
+  "version": "0.1.12",
   "git": "",
   "url": "",
-  "files": [
-    "main.py",
-    "setup.sh"
-  ],
-  "supported_hardware_architectures": [
-    "cpu",
-    "cuda",
-    "mlx"
-  ],
+  "files": ["main.py", "setup.sh"],
+  "supported_hardware_architectures": ["cpu", "cuda", "mlx"],
   "_dataset": true,
   "_dataset_display_message": "Please upload a dataset file with columns: 'input', 'output', 'expected_output'. The context column is optional if using metrics which don't require it.",
   "setup-script": "setup.sh",

api/transformerlab/plugins/common-eleuther-ai-lm-eval-harness-mlx/index.json

@@ -5,16 +5,11 @@
   "plugin-format": "python",
   "type": "evaluator",
   "evalsType": "model",
-  "version": "0.1.12",
+  "version": "0.1.13",
   "git": "https://github.com/chimezie/lm-evaluation-harness-mlx",
   "url": "https://github.com/chimezie/lm-evaluation-harness-mlx",
-  "supported_hardware_architectures": [
-    "mlx"
-  ],
-  "files": [
-    "main.py",
-    "setup.sh"
-  ],
+  "supported_hardware_architectures": ["mlx"],
+  "files": ["main.py", "setup.sh"],
   "_dataset": false,
   "setup-script": "setup.sh",
   "parameters": {
@@ -299,9 +294,7 @@
     },
     "limit": {
       "title": "Fraction of Samples to use for evaluation",
-      "type": [
-        "number"
-      ],
+      "type": ["number"],
       "minimum": 0.0,
       "default": 1.0,
       "maximum": 1.0,

api/transformerlab/plugins/common-eleuther-ai-lm-eval-harness/index.json

@@ -5,17 +5,11 @@
   "plugin-format": "python",
   "type": "evaluator",
   "evalsType": "model",
-  "version": "0.1.15",
+  "version": "0.1.16",
   "git": "https://github.com/EleutherAI/lm-evaluation-harness",
   "url": "https://github.com/EleutherAI/lm-evaluation-harness",
-  "supported_hardware_architectures": [
-    "cuda",
-    "amd"
-  ],
-  "files": [
-    "main.py",
-    "setup.sh"
-  ],
+  "supported_hardware_architectures": ["cuda", "amd"],
+  "files": ["main.py", "setup.sh"],
   "_dataset": false,
   "setup-script": "setup.sh",
   "parameters": {
@@ -300,9 +294,7 @@
     },
     "limit": {
       "title": "Number of samples (Enter a floating point between 0 and 1. Set as 1 to get all samples)",
-      "type": [
-        "number"
-      ],
+      "type": ["number"],
       "minimum": 0.0,
       "default": 1.0,
       "maximum": 1.0,

api/transformerlab/plugins/dataset_imagegen/index.json

@@ -4,13 +4,10 @@
   "description": "Generate images using a text-to-image model from a set of user-provided prompts.",
   "plugin-format": "python",
   "type": "generator",
-  "version": "0.1.6",
+  "version": "0.1.7",
   "git": "",
   "url": "",
-  "files": [
-    "main.py",
-    "setup.sh"
-  ],
+  "files": ["main.py", "setup.sh"],
   "supported_hardware_architectures": [],
   "_dataset": true,
   "setup-script": "setup.sh",

api/transformerlab/plugins/deepeval_llm_judge/index.json

@@ -5,22 +5,14 @@
   "plugin-format": "python",
   "evalsType": "dataset",
   "type": "evaluator",
-  "version": "0.2.17",
+  "version": "0.2.18",
   "git": "https://github.com/confident-ai/deepeval",
   "url": "https://github.com/confident-ai/deepeval",
-  "files": [
-    "main.py",
-    "setup.sh"
-  ],
+  "files": ["main.py", "setup.sh"],
   "_dataset": true,
   "_dataset_display_message": "Please upload a dataset file with columns: 'input', 'output', 'expected_output'. The context column is optional if using metrics which don't require it.",
   "setup-script": "setup.sh",
-  "supported_hardware_architectures": [
-    "cpu",
-    "cuda",
-    "mlx",
-    "amd"
-  ],
+  "supported_hardware_architectures": ["cpu", "cuda", "mlx", "amd"],
   "parameters": {
     "generation_model": {
       "title": "Model which will act as Judge LLM",
@@ -64,20 +56,15 @@
           "include_context": {
             "type": "string",
             "title": "Include Context while evaluating?",
-            "enum": [
-              "Yes",
-              "No"
-            ],
+            "enum": ["Yes", "No"],
             "default": "No"
           }
         }
       }
     },
     "limit": {
       "title": "Fraction of samples",
-      "type": [
-        "number"
-      ],
+      "type": ["number"],
       "minimum": 0.0,
       "default": 1.0,
       "maximum": 1.0,

api/transformerlab/plugins/deepeval_objective/index.json

@@ -5,19 +5,11 @@
   "plugin-format": "python",
   "type": "evaluator",
   "evalsType": "dataset",
-  "version": "0.2.14",
+  "version": "0.2.15",
   "git": "https://github.com/confident-ai/deepeval",
   "url": "https://github.com/confident-ai/deepeval",
-  "files": [
-    "main.py",
-    "setup.sh"
-  ],
-  "supported_hardware_architectures": [
-    "cpu",
-    "cuda",
-    "mlx",
-    "amd"
-  ],
+  "files": ["main.py", "setup.sh"],
+  "supported_hardware_architectures": ["cpu", "cuda", "mlx", "amd"],
   "_dataset": true,
   "_dataset_display_message": "Please upload a dataset file with columns: 'input', 'output', 'expected_output'. The context column is optional if using metrics which don't require it.",
   "setup-script": "setup.sh",
@@ -36,9 +28,7 @@
     },
     "limit": {
       "title": "Fraction of samples to evaluate",
-      "type": [
-        "number"
-      ],
+      "type": ["number"],
       "minimum": 0.0,
       "default": 1.0,
       "maximum": 1.0,