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This PR detects embedding models and sets batch_size = context_size so the full input fits in a single batch. Previously, if batch size was smaller than the input, tokens could be split across batches and cause a SIGTRAP crash. This change ensures all tokens stay in one batch and prevents crashes. Fixes: #12938 #13054 Co-authored-by: Jesse Gross <jesse@ollama.com>
runner
Note: this is a work in progress
A minimial runner for loading a model and running inference via a http web server.
./runner -model <model binary>
Completion
curl -X POST -H "Content-Type: application/json" -d '{"prompt": "hi"}' http://localhost:8080/completion
Embeddings
curl -X POST -H "Content-Type: application/json" -d '{"prompt": "turn me into an embedding"}' http://localhost:8080/embedding