![]() It is the opposite of git branch, which creates a branch. Git merge is an operation to merge two different branches. The commit –amend would not have changed the commit-id, and so it would not change the parent, so it fails. Here it re-chains my commit on top of a different commit than the one I started with. Cherry-pick is a change-parent operation and changes commit-id = hash(parent-commit-id + changes). The rebase command is composed of multiple cherry-pick commands. You must edit all merge conflicts and then mark them as resolved using git add $ git add file1 file2 $ git rebase -continue Find the conflicting files and edit them to resolve conflicts. $ git reset -merge $ git rebase First, rewinding head to replay your work on top of it. To recover from this situation, first squash the unnecessary merge and then do a rebase. The problem is the pull step, which implicitly does a fetch+merge and where the merge fails. $ git commit -amend fatal: You are in the middle of a merge - cannot amend. $ git rebase First, rewinding head to replay your work on top of it. Applying: change name Using index info to reconstruct a base tree. M file1 Falling back to patching base and 3-way merge. Auto-merging file1 CONFLICT (content): try git pull -rebase Auto-merging file1 CONFLICT (content): Merge conflict in file1 Automatic merge failed fix conflicts and then commit the result.Īt this point, I resolve the commits and attempt a git commit –amend. How do I replay my changes on top of changes from “xyz” in “abc” ? Here’s a seemingly obvious command to try: $ git pull origin abc // tldr don't do this. But before these changes are merged, another party merged changes from a branch “xyz” into “abc”. This fired a build and a code-review after which the code is ready to be merged. Let’s say I made changes to branch “abc”, committed and pushed them. LLM Inferencing is h… on Weights vs Activationsįeature Vectors, Emb… on ML Transformer and GPT-2 …Įthereum Security an… on SHA-3 Hash Construction LLM evolution – Anth… on LLM Inferencing is hard… ![]() DevSecOps – Securing the Software Supply Chain.OpenAI scaling kubernetes cluster to 7500 nodes. ![]() Reinforcement learning – optimal control theory, policies, RLLib, Ray, DeepRacer, OpenAI Gym.Security of Solidity Smart Contracts using DistilBERT.Hugging Face – AI models and datasets hub.Feature Vectors, Embeddings, Vector Databases, Feature Stores.LLM Inferencing is hard – tools and techniques.LLM evolution – Anthropic, AI21, Cohere, GPT-4. ![]()
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