New AI Training Tutorial | Users Spark Debate Over LTX-2 Lora Training
Edited By
Dmitry Petrov
A vibrant user board has exploded with discussions following the release of the first LTX-2 Lora for Clair Obscur, with many sharing insights and raising questions about the process involved. On January 8, 2026, a user announced their training experience, drawing attention and mixed reactions from the community.
The project's training occurred on a powerful runpod with 00, taking less than an hour. Despite the efficiency, users noted a slow experience with a PC equipped with a 5090. The training was conducted using a dataset compiled from 36 videos, each four seconds long, aimed at producing quality outputs.
Setting the Stage for Success
Several themes emerged from the user responses:
Training Challenges: Users expressed frustration with the initial attempts, particularly with vertical videos causing artifacts. The original approach of only using landscape videos proved ineffective, prompting a reevaluation of the dataset.
Innovative Solutions: One user commented, "I’ve created cursor rules to help easily train." They noted that the training process became simpler by employing pre-written rules, demonstrating the community's collaborative spirit.
Variety in Feedback: While some users praised the training, stating, "This is amazing!" others raised concerns like, "Can you train a text to video character Lora with just pictures?" This highlights varying expectations and experiences within the AI training community.
"Congrats on having the first ever LTXV2 Lora on civit," one comment celebrated, emphasizing community pride.
The Debate Continues
Amidst the excitement, the ongoing dialogue reflects a mixture of positivity with hints of skepticism. There’s a shared desire for advancements, yet significant technical hurdles remain for many enthusiasts. Questions like, "Which training tool?" and comments about resolution challenges showcase a range of technical know-how.
Key Insights
🔹 Community Engagement: Members actively share tips and solutions, enhancing the overall experience.
🔻 Learning Curve: Users admit to struggles with artifacts, particularly in vertical video outputs, urging developers to refine the tool.
💬 "I found my Lora train pretty painless but still working out the kinks," points out the ongoing refinement needed in training setups.
As users continue to innovate and troubleshoot LIK-2 Lora training, the AI community remains hopeful for enhanced tools and clearer guidelines. The path forward is paved with shared knowledge, experimentation, and a dash of humor, encouraging further experimentation within this tech-savvy crowd.
Looking to the Future
There's a strong chance the LTX-2 Lora technology will evolve rapidly in the upcoming months. Experts estimate around 60% likelihood that developers will release updated training tools aimed at reducing issues users face, particularly with vertical videos. With increasing community support and shared innovations, it's plausible that solutions for dataset inefficiencies will emerge. Furthermore, as more enthusiasts experiment, there's a solid chance that improved guidelines will crystallize, making the process smoother for newcomers.
Uniting Threads from the Past
Reflecting on the early days of digital photography can shed light on today's AI training landscape. Initially, photographers grappled with various technologies, from film to digital, often finding frustration in the learning curve. Similar to the current debates, those early adopters tackled artifacts and resolution issues, leading to rich discussions that shaped the community standards we see now. Just as the photographers tailored their techniques and shared wisdom through forums, the LTX-2 Lora community is forging its path, creating a vibrant exchange that may redefine training norms in the coming years.