remove research docs references (#178)

Remove research readmes references.

Signed-off-by: shanjiaz <[email protected]>

Author: shanjiaz

README.md

@@ -193,9 +193,9 @@ print(speculators.__version__)
 
 Here you can find links to our research implementations. These provide prototype code for immediate enablement and experimentation, with plans for productization into the main package soon.
 
-- [eagle3](https://github.com/neuralmagic/speculators/tree/main/research/eagle3): This implementation trains models similar to the EAGLE 3 architecture, specifically utilizing the Train Time Test method.
+- eagle3: This implementation trains models similar to the EAGLE 3 architecture, specifically utilizing the Train Time Test method.
 
-- [hass](https://github.com/neuralmagic/speculators/tree/main/research/hass): This implementation trains models that are a variation on the EAGLE 1 architecture using the [HASS](https://github.com/HArmonizedSS/HASS) method.
+- hass: This implementation trains models that are a variation on the EAGLE 1 architecture using the [HASS](https://github.com/HArmonizedSS/HASS) method.
 
 ## License
 

docs/index.md

@@ -101,5 +101,5 @@ VLLM_USE_V1=1 vllm serve RedHatAI/Qwen3-8B-speculator.eagle3
 
 Speculators includes prototype implementations of cutting-edge speculative decoding research:
 
-- **[EAGLE 3](https://github.com/neuralmagic/speculators/blob/main/research/eagle3/README.md)**: Train Time Test method implementation for advanced token speculation
-- **[HASS](https://github.com/neuralmagic/speculators/blob/main/research/hass/README.md)**: EAGLE 1 architecture variation using the HASS training method
+- **EAGLE 3**: Train Time Test method implementation for advanced token speculation
+- **HASS**: EAGLE 1 architecture variation using the HASS training method

examples/README.md

@@ -1,6 +1,6 @@
 # Training
 
-Speculators currently supports training of Eagle, Eagle 3 and HASS-style speculative decoders. This functionality is still under development and includes the necessary data generation and training steps required to produce the models. Examples of the training process can be found under the [`research`](https://github.com/neuralmagic/speculators/tree/main/research) directory for [Eagle 3](https://github.com/neuralmagic/speculators/blob/main/research/eagle3/README.md) and [HASS](https://github.com/neuralmagic/speculators/blob/main/research/hass/README.md).
+Speculators currently supports training of Eagle, Eagle 3 and HASS-style speculative decoders. This functionality is still under development and includes the necessary data generation and training steps required to produce the models. Examples of the training process can be found under the research directory for Eagle 3 and HASS.
 
 # Conversion
 

pyproject.toml

@@ -129,7 +129,7 @@ warn_redundant_casts = true
 warn_unused_ignores = false
 show_error_codes = true
 namespace_packages = true
-exclude = ["venv", ".tox", "build", "dist", "research"]
+exclude = ["venv", ".tox", "build", "dist"]
 
 # Silence "type import errors" as our 3rd-party libs does not have types
 # Check: https://mypy.readthedocs.io/en/latest/config_file.html#import-discovery
@@ -235,19 +235,6 @@ select = [
     "BLE001", # allow catching Exception for conversion errors
 ]
 
-"research/**/*.py" = [
-    "PTH",  # ignore using os.* instead of Path errors
-    "T20",  # ignore usage of print statement errors
-    "PLR",  # ignore code complexity errors
-    "NPY",  # ignore numpy formatting/usage errors
-    "E722",  # allow bare exception catching
-    "C90",  # ignore code complexity errors
-    "PGH004",  # allow general style ignores
-    "ERA001", # allow commented-out code
-    "N80",  # allow upper case names
-    "PLC0415", # ignore import not at top of file errors
-]
-
 [tool.ruff.lint.isort]
 known-first-party = ["speculators", "tests"]