Modelers.cn has added amd/Gumiho-llama3-8b, a fine-tune of Meta's Llama 3 8B published under an Apache 2.0 licence. For English-speaking developers who have not yet explored the Huawei Ascend…

If you build on Huawei's Ascend stack, you will already know that large open-weight checkpoints are thinner on the ground than they are on the big Western hubs. Gumiho-llama3-70b, published on…

Llama3 -> MCP -> foothills of the singularity

Cloudflare Workers + Llama 3 8B reemplazaron las APIs centralizadas de este creador. Show notes automáticas, menos latencia, mismo flujo creativo.

Modelers.cn, the Huawei/Ascend AI ecosystem platform, has picked up a GGUF build of NVIDIA's ChatQA 2 8B — listed as DevQuasar/Llama3-ChatQA-2-8B-GGUF — and it is worth a look if you want a local…

Yes. For open models, “model and version” has to mean more than a name like llama3:8b, because local tags can be repointed and one name can cover several quantizations. What I’d record per run: * weights identity: Hub repo id plus commit revision, and the sha256 of the file actually loaded, including the quantization * runtime and version (llama.cpp build, vLLM, Ollama) and the sampling parameters * a version or hash of the system prompt, agent config and tool definitions * one entry per tool call: tool name, arguments, result status, and a call/request ID that the downstream system logs as well, so the two sides can be joined * the trigger, any human approval (approver plus record ID), and token counts On standards: the OpenTelemetry GenAI semantic conventions define agent and tool-execution spans and attributes such as gen_ai.request.model, gen_ai.response.model, gen_ai.tool.call.id and token usage. They’re still marked Development, so pin the version you emit. For audit purposes, write the log to append-only storage that the agent’s own credentials can’t modify or delete.

Llama 3+ inference in pure Java. Contribute to mukel/llama3.java development by creating an account on GitHub.

Modelers.cn has a new GGUF package for developers curious about faster inference: DevQuasar/facebook.layerskip-llama3-8B-GGUF. At heart it is a quantised re-upload of Meta's LayerSkip-Llama3-8B…

_This is a submission for the Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle_ ## What I Built A lightning-fast, sleek slate-themed document parser built using FastAPI, LangChain, and Groq open-weights framework. 🌐 Link : https://docuscan-ai.onrender.com/ ## Code ## shaikhomarabdulmajid-spec / docuscan-ai ### # docuscan-ai View on GitHub ## 🛠️ My Tech Stack & Open-Source Core * **AI Core Framework:** Llama 3 (`llama3-70b-8192`) running via the hyper-fast **Groq Cloud API**. * **Orchestration Layer:** **FastAPI** + **LangChain Core** prompt modeling pipelines. * **Frontend Dashboard:** Custom deep-slate responsive user interface built using **Tailwind CSS**. * **Deployment Platform:** Hosted securely as a cloud application using **Render Web Services**. ## Why Does Open Innovation Matter? Keeps your personal documents **with you**. ## Prize Categories Render

Prompts cortos, show notes en markdown y Llama 3 en Cloudflare Workers: qué cuenta el autor de PodCrisp, qué está confirmado y qué falta medir.

If you are a Windows developer with an AMD Radeon GPU, Modelers.cn has just posted something quietly useful: amd/llama3-8b-instruct-dml-int4-awq-block-128-directml. It is a 4-bit INT4 AWQ-quantised…

MLCommons has released MLPerf Storage 3.0 results, with XSKY’s MeshFS debuting to claim nine first-place finishes in the parallel file system track using a single three-node EC configuration across large-file, massive-small-file and Llama3 405B checkpoint workloads.

MLCommons has released MLPerf Storage 3.0 results, with XSKY's MeshFS making its debut and claiming nine first places in the parallel file storage category. The vendor-backed analysis argues that a three-node EC configuration delivers competitive performance and hardware cost-efficiency across large-file, small-file and Llama3 405B checkpoint workloads.