README updated

Author: prishajain1

README.md

@@ -17,6 +17,7 @@
 [![Unit Tests](https://github.com/google/maxtext/actions/workflows/UnitTests.yml/badge.svg)](https://github.com/AI-Hypercomputer/maxdiffusion/actions/workflows/UnitTests.yml)
 
 # What's new?
+- **`2026/1/15`**: Wan2.1 and Wan2.2 Img2vid generation is now supported
 - **`2025/11/11`**: Wan2.2 txt2vid generation is now supported
 - **`2025/10/10`**: Wan2.1 txt2vid training and generation is now supported.
 - **`2025/10/14`**: NVIDIA DGX Spark Flux support.
@@ -482,19 +483,38 @@ To generate images, run the following command:
 
   Although not required, attaching an external disk is recommended as weights take up a lot of disk space. [Follow these instructions if you would like to attach an external disk](https://cloud.google.com/tpu/docs/attach-durable-block-storage).
 
+  ### Text2Vid
+
   ```bash
   HF_HUB_CACHE=/mnt/disks/external_disk/maxdiffusion_hf_cache/
   LIBTPU_INIT_ARGS="--xla_tpu_enable_async_collective_fusion=true --xla_tpu_enable_async_collective_fusion_fuse_all_reduce=true --xla_tpu_enable_async_collective_fusion_multiple_steps=true --xla_tpu_overlap_compute_collective_tc=true --xla_enable_async_all_reduce=true" HF_HUB_ENABLE_HF_TRANSFER=1 python src/maxdiffusion/generate_wan.py   src/maxdiffusion/configs/base_wan_14b.yml   attention="flash"   num_inference_steps=50   num_frames=81   width=1280   height=720   jax_cache_dir=gs://jfacevedo-maxdiffusion/jax_cache/   per_device_batch_size=.125   ici_data_parallelism=2   ici_fsdp_parallelism=2   flow_shift=5.0   enable_profiler=True   run_name=wan-inference-testing-720p   output_dir=gs:/jfacevedo-maxdiffusion   fps=16   flash_min_seq_length=0   flash_block_sizes='{"block_q" : 3024, "block_kv_compute" : 1024, "block_kv" : 2048, "block_q_dkv": 3024, "block_kv_dkv" : 2048, "block_kv_dkv_compute" : 2048, "block_q_dq" : 3024, "block_kv_dq" : 2048 }' seed=118445
   ```
+
+  ### Img2Vid
+
+   ```bash
+  HF_HUB_CACHE=/mnt/disks/external_disk/maxdiffusion_hf_cache/
+  LIBTPU_INIT_ARGS="--xla_tpu_enable_async_collective_fusion=true --xla_tpu_enable_async_collective_fusion_fuse_all_reduce=true --xla_tpu_enable_async_collective_fusion_multiple_steps=true --xla_tpu_overlap_compute_collective_tc=true --xla_enable_async_all_reduce=true" HF_HUB_ENABLE_HF_TRANSFER=1 python src/maxdiffusion/generate_wan.py   src/maxdiffusion/configs/base_wan_i2v_14b.yml   attention="flash"   num_inference_steps=30   num_frames=81   width=832   height=480   jax_cache_dir=gs://jfacevedo-maxdiffusion/jax_cache/   per_device_batch_size=.125   ici_data_parallelism=2   ici_fsdp_parallelism=2   flow_shift=3.0   enable_profiler=True   run_name=wan-i2v-inference-testing-480p   output_dir=gs:/jfacevedo-maxdiffusion   fps=16   flash_min_seq_length=0   flash_block_sizes='{"block_q" : 3024, "block_kv_compute" : 1024, "block_kv" : 2048, "block_q_dkv": 3024, "block_kv_dkv" : 2048, "block_kv_dkv_compute" : 2048, "block_q_dq" : 3024, "block_kv_dq" : 2048 }' seed=118445
+  ```
+
   ## Wan2.2
 
   Although not required, attaching an external disk is recommended as weights take up a lot of disk space. [Follow these instructions if you would like to attach an external disk](https://cloud.google.com/tpu/docs/attach-durable-block-storage).
 
+  ### Text2Vid
+
   ```bash
   HF_HUB_CACHE=/mnt/disks/external_disk/maxdiffusion_hf_cache/
   LIBTPU_INIT_ARGS="--xla_tpu_enable_async_collective_fusion=true --xla_tpu_enable_async_collective_fusion_fuse_all_reduce=true --xla_tpu_enable_async_collective_fusion_multiple_steps=true --xla_tpu_overlap_compute_collective_tc=true --xla_enable_async_all_reduce=true" HF_HUB_ENABLE_HF_TRANSFER=1 python src/maxdiffusion/generate_wan.py   src/maxdiffusion/configs/base_wan_27b.yml   attention="flash"   num_inference_steps=50   num_frames=81   width=1280   height=720   jax_cache_dir=gs://jfacevedo-maxdiffusion/jax_cache/   per_device_batch_size=.125   ici_data_parallelism=2   ici_fsdp_parallelism=2   flow_shift=5.0   enable_profiler=True   run_name=wan-inference-testing-720p   output_dir=gs:/jfacevedo-maxdiffusion   fps=16   flash_min_seq_length=0   flash_block_sizes='{"block_q" : 3024, "block_kv_compute" : 1024, "block_kv" : 2048, "block_q_dkv": 3024, "block_kv_dkv" : 2048, "block_kv_dkv_compute" : 2048, "block_q_dq" : 3024, "block_kv_dq" : 2048 }' seed=118445
   ```
 
+  ### Img2Vid
+
+  ```bash
+  HF_HUB_CACHE=/mnt/disks/external_disk/maxdiffusion_hf_cache/
+  LIBTPU_INIT_ARGS="--xla_tpu_enable_async_collective_fusion=true --xla_tpu_enable_async_collective_fusion_fuse_all_reduce=true --xla_tpu_enable_async_collective_fusion_multiple_steps=true --xla_tpu_overlap_compute_collective_tc=true --xla_enable_async_all_reduce=true" HF_HUB_ENABLE_HF_TRANSFER=1 python src/maxdiffusion/generate_wan.py   src/maxdiffusion/configs/base_wan_i2v_27b.yml   attention="flash"   num_inference_steps=30   num_frames=81   width=832   height=480   jax_cache_dir=gs://jfacevedo-maxdiffusion/jax_cache/   per_device_batch_size=.125   ici_data_parallelism=2   ici_fsdp_parallelism=2   flow_shift=3.0   enable_profiler=True   run_name=wan-i2v-inference-testing-480p   output_dir=gs:/jfacevedo-maxdiffusion   fps=16   flash_min_seq_length=0   flash_block_sizes='{"block_q" : 3024, "block_kv_compute" : 1024, "block_kv" : 2048, "block_q_dkv": 3024, "block_kv_dkv" : 2048, "block_kv_dkv_compute" : 2048, "block_q_dq" : 3024, "block_kv_dq" : 2048 }' seed=118445
+  ```
+
   ## Flux
 
   First make sure you have permissions to access the Flux repos in Huggingface.