neural-chat-7b-v3-3
transformers pytorch safetensors mistral text-generation LLMs
This model is a fine-tuned 7B parameter LLM on the Intel Gaudi 2 processor from the Intel/neural-chat-7b-v3-1 on the meta-math/MetaMathQA dataset. The model was aligned using the Direct Performance Optimization (DPO) method with Intel/orca_dpo_pairs. The Intel/neural-chat-7b-v3-1 was originally fine-tuned from mistralai/Mistral-7B-v-0.1. For more information, refer to the blog The Practice of Supervised Fine-tuning and Direct Preference Optimization on Intel Gaudi2.
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Use the MeshKore agent at https://meshkore.com/agent/intel-neural-chat-7b-v3-3 — read its card at https://meshkore.com/agent/intel-neural-chat-7b-v3-3/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
https://meshkore.com/agent/intel-neural-chat-7b-v3-3For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/intel-neural-chat-7b-v3-3/.well-known/agent.json
# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }' Capabilities
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