refactor: move all llama code to models/llama out of meta reference (#1887)

# What does this PR do?

Move around bits. This makes the copies from llama-models _much_ easier
to maintain and ensures we don't entangle meta-reference specific
tidbits into llama-models code even by accident.

Also, kills the meta-reference-quantized-gpu distro and rolls
quantization deps into meta-reference-gpu.

## Test Plan

```
LLAMA_MODELS_DEBUG=1 \
  with-proxy llama stack run meta-reference-gpu \
  --env INFERENCE_MODEL=meta-llama/Llama-4-Scout-17B-16E-Instruct \
   --env INFERENCE_CHECKPOINT_DIR=<DIR> \
   --env MODEL_PARALLEL_SIZE=4 \
   --env QUANTIZATION_TYPE=fp8_mixed
```

Start a server with and without quantization. Point integration tests to
it using:

```
pytest -s -v  tests/integration/inference/test_text_inference.py \
   --stack-config http://localhost:8321 --text-model meta-llama/Llama-4-Scout-17B-16E-Instruct
```

llama_stack/apis/inference/inference.py

@@ -25,15 +25,64 @@ from llama_stack.apis.models import Model
 from llama_stack.apis.telemetry.telemetry import MetricResponseMixin
 from llama_stack.models.llama.datatypes import (
     BuiltinTool,
-    SamplingParams,
     StopReason,
     ToolCall,
     ToolDefinition,
+    ToolParamDefinition,
     ToolPromptFormat,
 )
 from llama_stack.providers.utils.telemetry.trace_protocol import trace_protocol
 from llama_stack.schema_utils import json_schema_type, register_schema, webmethod
 
+register_schema(ToolCall)
+register_schema(ToolParamDefinition)
+register_schema(ToolDefinition)
+
+
+@json_schema_type
+class GreedySamplingStrategy(BaseModel):
+    type: Literal["greedy"] = "greedy"
+
+
+@json_schema_type
+class TopPSamplingStrategy(BaseModel):
+    type: Literal["top_p"] = "top_p"
+    temperature: Optional[float] = Field(..., gt=0.0)
+    top_p: Optional[float] = 0.95
+
+
+@json_schema_type
+class TopKSamplingStrategy(BaseModel):
+    type: Literal["top_k"] = "top_k"
+    top_k: int = Field(..., ge=1)
+
+
+SamplingStrategy = Annotated[
+    Union[GreedySamplingStrategy, TopPSamplingStrategy, TopKSamplingStrategy],
+    Field(discriminator="type"),
+]
+register_schema(SamplingStrategy, name="SamplingStrategy")
+
+
+@json_schema_type
+class SamplingParams(BaseModel):
+    """Sampling parameters.
+
+    :param strategy: The sampling strategy.
+    :param max_tokens: The maximum number of tokens that can be generated in the completion. The token count of
+        your prompt plus max_tokens cannot exceed the model's context length.
+    :param repetition_penalty: Number between -2.0 and 2.0. Positive values penalize new tokens
+        based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.
+    :param stop: Up to 4 sequences where the API will stop generating further tokens.
+        The returned text will not contain the stop sequence.
+    """
+
+    strategy: SamplingStrategy = Field(default_factory=GreedySamplingStrategy)
+
+    max_tokens: Optional[int] = 0
+    repetition_penalty: Optional[float] = 1.0
+    stop: Optional[List[str]] = None
+
 
 class LogProbConfig(BaseModel):
     """
@@ -48,18 +97,18 @@ class QuantizationType(Enum):
     """Type of model quantization to run inference with.
 
     :cvar bf16: BFloat16 typically this means _no_ quantization
-    :cvar fp8: 8-bit floating point quantization
-    :cvar int4: 4-bit integer quantization
+    :cvar fp8_mixed: 8-bit floating point quantization with mixed precision
+    :cvar int4_mixed: 4-bit integer quantization with mixed precision
     """
 
     bf16 = "bf16"
-    fp8 = "fp8"
-    int4 = "int4"
+    fp8_mixed = "fp8_mixed"
+    int4_mixed = "int4_mixed"
 
 
 @json_schema_type
 class Fp8QuantizationConfig(BaseModel):
-    type: Literal["fp8"] = "fp8"
+    type: Literal["fp8_mixed"] = "fp8_mixed"
 
 
 @json_schema_type
@@ -75,7 +124,7 @@ class Int4QuantizationConfig(BaseModel):
     :param scheme: Quantization scheme to use. Defaults to "int4_weight_int8_dynamic_activation"
     """
 
-    type: Literal["int4"] = "int4"
+    type: Literal["int4_mixed"] = "int4_mixed"
     scheme: Optional[str] = "int4_weight_int8_dynamic_activation"