unilm
llm-vscode-inference-server
unilm | llm-vscode-inference-server | |
---|---|---|
43 | 1 | |
18,689 | 44 | |
2.0% | - | |
9.0 | 5.3 | |
12 days ago | 8 months ago | |
Python | Python | |
MIT License | Apache License 2.0 |
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unilm
- The Era of 1-Bit LLMs: Training_Tips, Code And_FAQ [pdf]
- The Era of 1-Bit LLMs: Training Tips, Code and FAQ
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The Era of 1-bit LLMs: ternary parameters for cost-effective computing
+1 On this, the real proof would have been testing both models side-by-side.
It seems that it may be published on GitHub [1] according to HuggingFace [2].
[1] https://github.com/microsoft/unilm/tree/master/bitnet
[2] https://huggingface.co/papers/2402.17764
- I'm an Old Fart and AI Makes Me Sad
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On building a semantic search engine
e5-mistral is essentially a distillation from gpt-4 to a smaller model. You can see here https://github.com/microsoft/unilm/blob/16da2f193b9c1dab0a69...
they actually have custom prompts for each dataset being tested.
Question would be, if you haven't seen the task before, what is a good prompt to prepend for your task?
IMO e5-mistral is overfit to MTEB
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Leveraging GPT-4 for PDF Data Extraction: A Comprehensive Guide
Layout LM v1, v2 and v3 models [ Github ] DocBERT [ Github ]
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Microsoft Publishes LongNet: Scaling Transformers to 1,000,000,000 Tokens
The repository is available here.
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Recommended open LLMs with image input modality?
It is missing kosmos-2. I remember its image captioning was(demo currently down) really good and it's almost as fast as llava and lavin.
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LongNet: Scaling Transformers to 1,000,000,000 Tokens
Should be this: https://github.com/microsoft/unilm/
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[R] LongNet: Scaling Transformers to 1,000,000,000 Tokens
This is from Microsoft Research (Asia). https://aka.ms/GeneralAI
llm-vscode-inference-server
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Replit's new AI Model now available on Hugging Face
Requests for code generation are made via an HTTP request.
You can use the Hugging Face Inference API or your own HTTP endpoint, provided it adheres to the API specified here[1] or here[2]."
It's fairly easy to use your own model locally with the plugin. You can just use the one of the community developed inference servers, which are listed at the bottom of the page, but here's the links[3] to both[4].
[1]: https://huggingface.co/docs/api-inference/detailed_parameter...
[2]: https://huggingface.github.io/text-generation-inference/#/Te...
[3]: https://github.com/wangcx18/llm-vscode-inference-server
[4]: https://github.com/wangcx18/llm-vscode-inference-server
What are some alternatives?
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
llmflows - LLMFlows - Simple, Explicit and Transparent LLM Apps
ERNIE - Official implementations for various pre-training models of ERNIE-family, covering topics of Language Understanding & Generation, Multimodal Understanding & Generation, and beyond.
MetaGPT - 🌟 The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming
involution - [CVPR 2021] Involution: Inverting the Inherence of Convolution for Visual Recognition, a brand new neural operator
localpilot
gensim - Topic Modelling for Humans
refact - WebUI for Fine-Tuning and Self-hosting of Open-Source Large Language Models for Coding
maelstrom - A workbench for writing toy implementations of distributed systems.
ChatGLM2-6B - ChatGLM2-6B: An Open Bilingual Chat LLM | 开源双语对话语言模型
rasa - 💬 Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants
Chinese-LLaMA-Alpaca - 中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs)