Initial version porting the eden configs over to the new evo2 recipe (#1502)

### Description

This PR adds Eden (Llama 3.1) model support, Savanna/Vortex checkpoint
converters, and a standardized model naming convention to the Megatron
Bridge–based Evo2 recipe (`bionemo-recipes/recipes/evo2_megatron/`).

**Eden (Llama 3.1) model support**

- New `eden_provider.py` defining `EdenModelProvider` and size-specific
subclasses (`eden_7b` through `eden_35b`) that inherit from
`Llama31ModelProvider`.
- `train.py` now dispatches to `gpt_forward_step` for Eden models and
automatically disables `fp32_residual_connection` (incompatible with
standard TE `LayerNormLinear` layers — Hyena handles this via manual
dtype casting, but GPT/Llama does not).
- `infer.py` now initializes `ProcessGroupCollection` for non-Hyena
providers (required by `GPTModelProvider.provide()`) and uses
`StaticInferenceContext` instead of `HyenaInferenceContext` for Eden
models. The `flash_decode` attribute is guarded to Hyena-only.
- `predict.py` already worked architecture-agnostically via dynamic
model loading; no changes required.

**Checkpoint converters**

- `savanna_to_mbridge.py` — converts ARC Savanna `.pt` checkpoints
(local or downloaded from Hugging Face via `hf_hub_download`) into
MBridge distributed checkpoint format.
- `mbridge_to_vortex.py` — exports MBridge checkpoints to ARC's
single-file Vortex inference format, handling MLP weight splitting,
Hyena filter pole/residue computation, and TE layernorm key remapping.
- Both are registered as console scripts
(`evo2_convert_savanna_to_mbridge`, `evo2_export_mbridge_to_vortex`).

**Model naming convention**

The previous model size keys (`1b`, `7b`, `40b`, `7b_arc_longcontext`,
…) were ambiguous — `7b` referred to Striped Hyena while `7B` referred
to Llama. This PR replaces them with explicit, architecture-prefixed
keys:
- `evo2_*` for models matching public ARC checkpoints (e.g.
`evo2_1b_base`, `evo2_7b`, `evo2_40b_base`). `_base` = 8K context,
without it = 1M context.
- `striped_hyena_*_nv` for NVIDIA-modified Hyena variants.
- `eden_*` for Llama 3.1 variants.
- Added `evo2_20b` config based on `arcinstitute/savanna_evo2_20b`.

**Documentation updates**

- `README.md` — added model naming convention tables, Vortex export
section with round-trip example, updated all CLI examples to new model
keys.
- `checkpoint/README.md` — updated `--model-size` documentation.
- Both Jupyter notebooks (`zeroshot_brca1.ipynb`,
`fine-tuning-tutorial.ipynb`) — updated `MODEL_SIZE` and `--model-size`
references.

#### Usage

Training an Eden model:

```bash
torchrun --nproc-per-node 1 --no-python train_evo2 \
  --model-size eden_7b --num-layers 2 --max-steps 5 \
  --mock-data --seq-length 64 --mixed-precision-recipe bf16_mixed \
  --no-activation-checkpointing
```

Converting Savanna checkpoint to MBridge:

```bash
evo2_convert_savanna_to_mbridge \
  --savanna-ckpt-path arcinstitute/savanna_evo2_1b_base \
  --mbridge-ckpt-dir /tmp/mbridge_1b \
  --model-size evo2_1b_base \
  --tokenizer-path tokenizers/nucleotide_fast_tokenizer_256
```

Exporting MBridge to Vortex:

```bash
evo2_export_mbridge_to_vortex \
  --mbridge-ckpt-dir /tmp/mbridge_1b/iter_0000001 \
  --output-path /tmp/evo2_1b_vortex.pt \
  --model-size evo2_1b_base
```

### Type of changes

- [ ] Bug fix (non-breaking change which fixes an issue)
- [x] New feature (non-breaking change which adds functionality)
- [x] Refactor
- [x] Documentation update
- [ ] Other (please describe):

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<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->

## Summary by CodeRabbit

* **New Features**
* Added Eden (Llama 3.1) model family support alongside existing Hyena
models (11B–35B variants).
* Added checkpoint conversion utilities: Savanna-to-MBridge and
MBridge-to-Vortex exporters with CLI tools.

* **Documentation**
* Updated model naming convention with Evo2 prefixes (e.g.,
`evo2_1b_base`, `evo2_7b`).
* Expanded documentation for checkpoint conversion workflows and
available models.

* **Tests**
* Added comprehensive test coverage for model providers, checkpoint
conversions, and Eden inference/prediction workflows.

<!-- end of auto-generated comment: release notes by coderabbit.ai -->

---------

Signed-off-by: John St. John <jstjohn@nvidia.com>

Author: jstjohn

bionemo-recipes/recipes/evo2_megatron/README.md

@@ -7,7 +7,10 @@
 *.yaml
 
 # directories created during these notebook runs.
+evo2_20b_finetune/
+savanna_20b_download/
 nemo2_evo2_1b_8k/
+evo2_1b_bf16_mbridge/
 preprocessed_data/
 pretraining_demo/
 brca1_fasta_files/

bionemo-recipes/recipes/evo2_megatron/examples/.dockerignore

@@ -7,6 +7,8 @@
 *.yaml
 
 # directories created during these notebook runs.
+evo2_20b_finetune/
+savanna_20b_download/
 nemo2_evo2_1b_8k/
 evo2_1b_bf16_mbridge/
 preprocessed_data/