diff --git a/helpers/training/default_settings/safety_check.py b/helpers/training/default_settings/safety_check.py
index 8476b873..bd21e7ab 100644
--- a/helpers/training/default_settings/safety_check.py
+++ b/helpers/training/default_settings/safety_check.py
@@ -17,19 +17,22 @@ def safety_check(args, accelerator):
         # mulit-gpu safety checks & warnings
         if args.model_type == "lora" and args.lora_type == "standard":
             # multi-gpu PEFT checks & warnings
-            if "quanto" in args.base_model_precision:
+            if args.base_model_precision in ["fp8-quanto"]:
                 logger.error(
-                    "Quanto is incompatible with multi-GPU training on PEFT adapters. Use LORA_TYPE (--lora_type) lycoris for quantised multi-GPU training of LoKr models."
+                    f"{args.base_model_precision} is incompatible with multi-GPU training on PEFT LoRA."
+                    " Use LORA_TYPE (--lora_type) lycoris for quantised multi-GPU training of LoKr models in FP8."
                 )
-                sys.exit(1)
+                args.base_model_precision = "int8-quanto"
+                # sys.exit(1)
     if (
         args.base_model_precision in ["fp8-quanto", "int4-quanto"]
         and accelerator.state.dynamo_plugin.backend.lower() == "inductor"
     ):
         logger.warning(
-            f"{args.base_model_precision} is not supported with Dynamo backend. Switching to int8-quanto instead."
+            f"{args.base_model_precision} is not supported with Dynamo backend. Disabling Dynamo."
         )
-        args.base_model_precision = "int8-quanto"
+        from accelerate.utils import DynamoBackend
+        accelerator.state.dynamo_plugin.backend = DynamoBackend.NO
     if args.report_to == "wandb":
         if not is_wandb_available():
             raise ImportError(
diff --git a/helpers/training/quantisation/quanto_workarounds.py b/helpers/training/quantisation/quanto_workarounds.py
index 19fdce1a..86d3741e 100644
--- a/helpers/training/quantisation/quanto_workarounds.py
+++ b/helpers/training/quantisation/quanto_workarounds.py
@@ -6,10 +6,12 @@
     import optimum
     from optimum.quanto.library.extensions.cuda import ext as quanto_ext
 
-    @torch.library.custom_op(
-        "quanto::fp8_marlin_gemm", mutates_args=(), device_types=["cuda"]
-    )
-    def fp8_marlin_gemm(
+    # torch tells us to do this because 
+    torch._dynamo.config.optimize_ddp=False
+    # Save the original operator
+    original_gemm_f16f8_marlin = torch.ops.quanto.gemm_f16f8_marlin
+
+    def fp8_marlin_gemm_wrapper(
         a: torch.Tensor,
         b_q_weight: torch.Tensor,
         b_scales: torch.Tensor,
@@ -19,11 +21,11 @@ def fp8_marlin_gemm(
         size_n: int,
         size_k: int,
     ) -> torch.Tensor:
-        assert b_scales.dtype == torch.float16 or b_scales.dtype == torch.bfloat16
-        assert b_q_weight.dim() == 2
-        assert b_q_weight.dtype == torch.int32
-        return quanto_ext.lib.fp8_marlin_gemm(
-            a.to(b_scales.dtype),
+        # Ensure 'a' has the correct dtype
+        a = a.to(b_scales.dtype)
+        # Call the original operator
+        return original_gemm_f16f8_marlin(
+            a,
             b_q_weight,
             b_scales,
             workspace,
@@ -33,9 +35,11 @@ def fp8_marlin_gemm(
             size_k,
         )
 
-    optimum.quanto.library.extensions.cuda.fp8_marlin_gemm = fp8_marlin_gemm
-
-    class TinyGemmQBitsLinearFunction(optimum.quanto.tensor.function.QuantizedLinearFunction):
+    # Monkey-patch the operator
+    torch.ops.quanto.gemm_f16f8_marlin = fp8_marlin_gemm_wrapper
+    class TinyGemmQBitsLinearFunction(
+        optimum.quanto.tensor.function.QuantizedLinearFunction
+    ):
         @staticmethod
         def forward(ctx, input, other, bias):
             ctx.save_for_backward(input, other)
@@ -45,12 +49,16 @@ def forward(ctx, input, other, bias):
             out_features = other.shape[0]
             output_shape = input.shape[:-1] + (out_features,)
             output = torch._weight_int4pack_mm(
-                input.view(-1, in_features).to(dtype=other.dtype), other._data._data, other._group_size, other._scale_shift
+                input.view(-1, in_features).to(dtype=other.dtype),
+                other._data._data,
+                other._group_size,
+                other._scale_shift,
             )
             output = output.view(output_shape)
             if bias is not None:
                 output = output + bias
             return output
-        
+
     from optimum.quanto.tensor.weights import tinygemm
-    tinygemm.qbits.TinyGemmQBitsLinearFunction = TinyGemmQBitsLinearFunction
\ No newline at end of file
+
+    tinygemm.qbits.TinyGemmQBitsLinearFunction = TinyGemmQBitsLinearFunction
diff --git a/install/apple/poetry.lock b/install/apple/poetry.lock
index e70521e2..b3b9a16b 100644
--- a/install/apple/poetry.lock
+++ b/install/apple/poetry.lock
@@ -1184,7 +1184,7 @@ typing = ["mypy (>=1.0.0)", "types-setuptools"]
 
 [[package]]
 name = "lycoris_lora"
-version = "3.0.1.dev13"
+version = "3.0.1.dev14"
 description = "Lora beYond Conventional methods, Other Rank adaptation Implementations for Stable diffusion"
 optional = false
 python-versions = ">=3.10"
@@ -1201,7 +1201,7 @@ tqdm = "*"
 type = "git"
 url = "https://github.com/kohakublueleaf/lycoris"
 reference = "dev"
-resolved_reference = "6bea3d061e3730c2274f7f9d035a2757a9b0fd7d"
+resolved_reference = "8978355aa43164393736269416956f1974580166"
 
 [[package]]
 name = "markdown"
@@ -1759,7 +1759,7 @@ files = []
 develop = false
 
 [package.dependencies]
-huggingface-hub = "*"
+huggingface_hub = "*"
 ninja = "*"
 numpy = "*"
 safetensors = "*"
@@ -1773,7 +1773,7 @@ examples = ["accelerate", "datasets", "diffusers", "scipy", "sentencepiece", "to
 type = "git"
 url = "https://github.com/huggingface/optimum-quanto"
 reference = "HEAD"
-resolved_reference = "784b0cf609e4e04df1cb154e15a23ab33283fead"
+resolved_reference = "194150f384ae9244dd4eb86994f6c510200663f9"
 
 [[package]]
 name = "packaging"
diff --git a/install/github/poetry.lock b/install/github/poetry.lock
new file mode 100644
index 00000000..56eb221f
--- /dev/null
+++ b/install/github/poetry.lock
@@ -0,0 +1,3994 @@
+# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
+
+[[package]]
+name = "absl-py"
+version = "2.1.0"
+description = "Abseil Python Common Libraries, see https://github.com/abseil/abseil-py."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "absl-py-2.1.0.tar.gz", hash = "sha256:7820790efbb316739cde8b4e19357243fc3608a152024288513dd968d7d959ff"},
+    {file = "absl_py-2.1.0-py3-none-any.whl", hash = "sha256:526a04eadab8b4ee719ce68f204172ead1027549089702d99b9059f129ff1308"},
+]
+
+[[package]]
+name = "accelerate"
+version = "0.34.2"
+description = "Accelerate"
+optional = false
+python-versions = ">=3.8.0"
+files = [
+    {file = "accelerate-0.34.2-py3-none-any.whl", hash = "sha256:d69159e2c4e4a473d14443b27d2d732929254e826b3ab4813b3785b5ac616c7c"},
+    {file = "accelerate-0.34.2.tar.gz", hash = "sha256:98c1ebe1f5a45c0a3af02dc60b5bb8b7d58d60c3326a326a06ce6d956b18ca5b"},
+]
+
+[package.dependencies]
+huggingface-hub = ">=0.21.0"
+numpy = ">=1.17,<3.0.0"
+packaging = ">=20.0"
+psutil = "*"
+pyyaml = "*"
+safetensors = ">=0.4.3"
+torch = ">=1.10.0"
+
+[package.extras]
+deepspeed = ["deepspeed"]
+dev = ["bitsandbytes", "black (>=23.1,<24.0)", "datasets", "diffusers", "evaluate", "hf-doc-builder (>=0.3.0)", "parameterized", "pytest (>=7.2.0,<=8.0.0)", "pytest-subtests", "pytest-xdist", "rich", "ruff (>=0.2.1,<0.3.0)", "scikit-learn", "scipy", "timm", "torchdata (>=0.8.0)", "torchpippy (>=0.2.0)", "tqdm", "transformers"]
+quality = ["black (>=23.1,<24.0)", "hf-doc-builder (>=0.3.0)", "ruff (>=0.2.1,<0.3.0)"]
+rich = ["rich"]
+sagemaker = ["sagemaker"]
+test-dev = ["bitsandbytes", "datasets", "diffusers", "evaluate", "scikit-learn", "scipy", "timm", "torchdata (>=0.8.0)", "torchpippy (>=0.2.0)", "tqdm", "transformers"]
+test-prod = ["parameterized", "pytest (>=7.2.0,<=8.0.0)", "pytest-subtests", "pytest-xdist"]
+test-trackers = ["comet-ml", "dvclive", "tensorboard", "wandb"]
+testing = ["bitsandbytes", "datasets", "diffusers", "evaluate", "parameterized", "pytest (>=7.2.0,<=8.0.0)", "pytest-subtests", "pytest-xdist", "scikit-learn", "scipy", "timm", "torchdata (>=0.8.0)", "torchpippy (>=0.2.0)", "tqdm", "transformers"]
+
+[[package]]
+name = "aiohappyeyeballs"
+version = "2.4.2"
+description = "Happy Eyeballs for asyncio"
+optional = false
+python-versions = ">=3.8"
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+
+[[package]]
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diff --git a/install/github/pyproject.toml b/install/github/pyproject.toml
new file mode 100644
index 00000000..6903e0bd
--- /dev/null
+++ b/install/github/pyproject.toml
@@ -0,0 +1,61 @@
+[tool.poetry]
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+iterutils = "^0.1.6"
+scipy = "^1.11.1"
+boto3 = "^1.35.24"
+pandas = "^2.2.3"
+botocore = "^1.35.24"
+urllib3 = "<1.27"
+torchsde = "^0.2.5"
+torchmetrics = "^1.1.1"
+colorama = "^0.4.6"
+numpy = "1.26"
+peft = "^0.12.0"
+tensorboard = "^2.17.1"
+regex = "^2023.12.25"
+huggingface-hub = "^0.23.3"
+optimum-quanto = {git = "https://github.com/huggingface/optimum-quanto"}
+torch-optimi = "^0.2.1"
+lycoris-lora = {git = "https://github.com/kohakublueleaf/lycoris", rev = "dev"}
+fastapi = {extras = ["standard"], version = "^0.115.0"}
+deepspeed = "^0.15.1"
+sentencepiece = "^0.2.0"
+torchao = "^0.5.0"
+
+
+[build-system]
+requires = ["poetry-core"]
+build-backend = "poetry.core.masonry.api"
+
+[[tool.poetry.source]]
+priority = "supplemental"
+name = "pytorch"
+url = "https://download.pytorch.org/whl/cpu"
+
+[[tool.poetry.source]]
+priority = "supplemental"
+name = "pytorch-nightly"
+url = "https://download.pytorch.org/whl/nightly/cpu"
diff --git a/install/rocm/poetry.lock b/install/rocm/poetry.lock
index 52b682fa..9f7bfcde 100644
--- a/install/rocm/poetry.lock
+++ b/install/rocm/poetry.lock
@@ -1169,7 +1169,7 @@ typing = ["mypy (>=1.0.0)", "types-setuptools"]
 
 [[package]]
 name = "lycoris_lora"
-version = "3.0.1.dev13"
+version = "3.0.1.dev14"
 description = "Lora beYond Conventional methods, Other Rank adaptation Implementations for Stable diffusion"
 optional = false
 python-versions = ">=3.10"
@@ -1186,7 +1186,7 @@ tqdm = "*"
 type = "git"
 url = "https://github.com/kohakublueleaf/lycoris"
 reference = "dev"
-resolved_reference = "a3eceaf2bff728a51e16d8e32f269615d849ef2d"
+resolved_reference = "8978355aa43164393736269416956f1974580166"
 
 [[package]]
 name = "markdown"
@@ -1735,7 +1735,7 @@ files = []
 develop = false
 
 [package.dependencies]
-huggingface-hub = "*"
+huggingface_hub = "*"
 ninja = "*"
 numpy = "*"
 safetensors = "*"
@@ -1749,7 +1749,7 @@ examples = ["accelerate", "datasets", "diffusers", "scipy", "sentencepiece", "to
 type = "git"
 url = "https://github.com/huggingface/optimum-quanto"
 reference = "HEAD"
-resolved_reference = "784b0cf609e4e04df1cb154e15a23ab33283fead"
+resolved_reference = "194150f384ae9244dd4eb86994f6c510200663f9"
 
 [[package]]
 name = "packaging"
diff --git a/poetry.lock b/poetry.lock
index 7c1a5a49..696f051c 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1613,7 +1613,7 @@ tqdm = "*"
 type = "git"
 url = "https://github.com/kohakublueleaf/lycoris"
 reference = "dev"
-resolved_reference = "6bea3d061e3730c2274f7f9d035a2757a9b0fd7d"
+resolved_reference = "8978355aa43164393736269416956f1974580166"
 
 [[package]]
 name = "markdown"
@@ -2143,7 +2143,7 @@ files = []
 develop = false
 
 [package.dependencies]
-huggingface_hub = "*"
+huggingface-hub = "*"
 ninja = "*"
 numpy = "*"
 safetensors = "*"
@@ -2157,7 +2157,7 @@ examples = ["accelerate", "datasets", "diffusers", "scipy", "sentencepiece", "to
 type = "git"
 url = "https://github.com/huggingface/optimum-quanto"
 reference = "HEAD"
-resolved_reference = "5f88400baec561a79cdb87311608981c17e4c368"
+resolved_reference = "194150f384ae9244dd4eb86994f6c510200663f9"
 
 [[package]]
 name = "packaging"
@@ -4032,13 +4032,9 @@ optional = false
 python-versions = ">=3.8"
 files = [
     {file = "torchvision-0.20.0.dev20240929+cu124-cp310-cp310-linux_x86_64.whl", hash = "sha256:f525a61b532baf70b9f798b46c951143ee2c103c529b83365a2995fb5a4d3aa6"},
-    {file = "torchvision-0.20.0.dev20240929+cu124-cp310-cp310-win_amd64.whl", hash = "sha256:f4a4fce7e0f98938682e2faae181d31553e5c05aa7892fc05fd2fb06673949f2"},
     {file = "torchvision-0.20.0.dev20240929+cu124-cp311-cp311-linux_x86_64.whl", hash = "sha256:255f7f5142b22430fd0c50ac53659dec98826e69576c449a5483d39446bbc471"},
-    {file = "torchvision-0.20.0.dev20240929+cu124-cp311-cp311-win_amd64.whl", hash = "sha256:3646651e57a25c4156f9cbc431ef112f88f29fac198167b3c3bbb21cfea43467"},
     {file = "torchvision-0.20.0.dev20240929+cu124-cp312-cp312-linux_x86_64.whl", hash = "sha256:ef9c0c3201b8f383e9cdbdb9908d61b9a06e066e707015ffd4e03c69d46a660d"},
-    {file = "torchvision-0.20.0.dev20240929+cu124-cp312-cp312-win_amd64.whl", hash = "sha256:31a1551aaf080e82205cd3a21583ab5a9f9a859f8fb2b45265ba741599ef97ef"},
     {file = "torchvision-0.20.0.dev20240929+cu124-cp39-cp39-linux_x86_64.whl", hash = "sha256:f3e2e23952c4e2f472e4301d4b2c7554d76ce45dece4d2cc33a34f99be39e75a"},
-    {file = "torchvision-0.20.0.dev20240929+cu124-cp39-cp39-win_amd64.whl", hash = "sha256:d892a3f2c3689806c72d9561c8be0495913c0422ca7739bb7a30eec1343e41e5"},
 ]
 
 [package.dependencies]
@@ -5014,4 +5010,4 @@ cffi = ["cffi (>=1.11)"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.10,<3.12"
-content-hash = "b7a29deccc162729660c6eb5e910ff1cc7abc2856594cda855b8185da7327ab8"
\ No newline at end of file
+content-hash = "b7a29deccc162729660c6eb5e910ff1cc7abc2856594cda855b8185da7327ab8"