#lmdeploy search results
🚀 Big news for #lmdeploy v0.10.1! 🥳Our #FP8 high-performance inference is no longer limited to the latest #GPUs. It now supports all #NVIDIA architectures from V100 onwards, bringing major speedups to more users. 🤗github.com/InternLM/lmdep…
🚀 Big news in #lmdeploy v0.3.0! We've optimized GQA inference, achieving 24+ RPS for #internlm2-7b & 17+ for internlm2-20b—1.8x faster than #vLLM! 🌟 Also, introducing support for #Qwen 1.5-MOE, #DBRX, & #DeepSeek-VL. 🥰Stay tuned for more! github.com/InternLM/lmdep…
🥳Say hello to the new face of lmdeploy! We hope you love it as much as we do! #lmdeploy 🤗github.com/InternLM/lmdep…
🥳Excited to announce that #OpenCompass is compatible with #LMDeploy 🤗Support Qwen-7B and XVERSE-13B ! Go to our leaderboard for more results! 😍(Preview) The feature of comparing models will soon be available on our platform. Stay tuned for more updates! github.com/InternLM/openc…
💡 Transform your LLM into a high-performing AI with #LMDeploy! 🔧 TurboMind: Speed with C++ & CUDA 🎨 PyTorch: Flexible, developer-friendly 🌐 REST APIs + CLI: Effortless integration From setup to advanced techniques, explore it all: medium.com/@omkamal/unlea… #AI #LLM #LLMOps
🥳#LMDeploy supports 4-bit quantized #LLM model inference, 2.4x faster than FP16 on #NVIDIA Geforce RTX 4090, which is the fastest open-source implementation as far as we know. 🤗Check this guide out for more detailed deployment information: github.com/InternLM/lmdep…
🤗The high throughput is guaranteed by deep optimized cuda kernels and a persistent-batch strategy. 🤗#LMDeploy models the inference of a conversational #LLM as a persistently running batch whose lifetime spans the entire serving process, hence naming it "persistent batch".
🥳#LMDeploy v0.0.8 has arrived with two incredible features: ✅ Access to all capabilities of #CodeLlama - including code completion, infilling, instruct / chat, and python specialist ✅ Support for both #Baichuan2-7B-Base and Baichuan2-7B-Chat 👉github.com/InternLM/lmdep…
🥰#lmdeploy v0.0.6 is now live! #LLM #AI ✅#Qwen-7B support with dynamic NTK scaling and logN scaling in turbomind ✅Tensor parallelism for W4A16 ✅Added an #OpenAI-like RESTful API ✅#Llama-2 70B 4-bit quantization 🥳Stay tuned for more exciting updates! github.com/InternLM/lmdep…
#lmdeploy #C++ LMDeploy is a toolkit for compressing, deploying, and serving LLMs. gtrending.top/content/3455/
#LMDeploy provides an OpenAI-compatible server, which means that it can be integrated into applications that use the OpenAI API. This makes it easy to switch from using OpenAI's services to running your own models on more affordable compute. vast.ai/article/servin…
Bonus Infra Stack (Infra teams love this): – Ollama: Local launcher with quant baked in – vLLM: API-compatible & batch-optimized – LMDeploy: Custom GPU serving – Llama.cpp: Great for mobile/edge Mix and match depending on your infra. #AIInfra2025 #Ollama #LMDeploy
🥳I just published Faster and More Efficient 4-bit quantized #LLM Model Inference. #LMDeploy 👉link.medium.com/rYLTnqEIiCb
link.medium.com
Faster and More Efficient 4-bit quantized LLM Model Inference
LMDeploy has released an exciting new feature — 4-bit quantization and inference. This not only trims down the model’s memory overhead to…
🥳#LMDeploy supports 4-bit quantized #LLM model inference, 2.4x faster than FP16 on #NVIDIA Geforce RTX 4090, which is the fastest open-source implementation as far as we know. 🤗Check this guide out for more detailed deployment information: github.com/InternLM/lmdep…
🥳An OpenAI-like RESTful API has been integrated to #LMDeploy. #LLMInference #RESTful-API #LLM 👉github.com/InternLM/lmdep… 🤗A Quick guide can be found from github.com/InternLM/lmdep…
🥳#LMDeploy support Llama3.1 and its Tool Calling. An example of calling "Wolfram Alpha" to perform complex mathematical calculations can be found from here. github.com/InternLM/lmdep… 😉Welcome to star LMDeploy! github.com/InternLM/lmdep… #LLaMA3 @AIatMeta @Meta
🥳#lmdeploy Release v0.0.7! ✅Flash attention 2 is now supported, boosting context decoding speed by approximately 45% ✅Token_id decoding has been optimized for better efficiency ✅The gemm-tunned script has been packed in the PyPI package 🤗github.com/InternLM/lmdep…
github.com
Release LMDeploy Release V0.0.7 · InternLM/lmdeploy
Highlights Flash attention 2 is supported, boosting context decoding speed by approximately 45% Token_id decoding has been optimized for better efficiency The gemm-tunned script has been packed in...
🧐Want to quickly deploy the #Llama2 models? 😍This article shows us how to quickly deploy the #Llama-2 models with #LMDeploy. 👉Let's get started! #LLM @MetaAI link.medium.com/Kv6YU3E8WBb
link.medium.com
Deploy Llama-2 models easily with LMDeploy!
This article will guide you on how to quickly deploy the Llama-2 models with LMDeploy.
🥳Thrilled to announce LMDeploy v0.1.0 is here! The inference now achieves ~900 request/s for llama-7b. 🤗A100 benchmarks link: github.com/InternLM/lmdep… 🤗GitHub link: github.com/InternLM/lmdep… #LMDeploy
github.com
Release LMDeploy Release V0.1.0 · InternLM/lmdeploy
What's Changed 🚀 Features Add extra_requires to reduce dependencies by @RunningLeon in #580 TurboMind 2 by @lzhangzz in #590 Support loading hf model directly by @irexyc in #685 convert model ...
🥳Significant update in #LMDeploy. #LLMInference 🤗Building on previous work of 4-bit quantized #LLM model inference, we've now added support for tensor parallelism 🤗Support Qwen-7B and Qwen-Chat-7B with dynamic NTK-RoPE scaling and dynamic logN scaling github.com/InternLM/lmdep…
🚀 Big news for #lmdeploy v0.10.1! 🥳Our #FP8 high-performance inference is no longer limited to the latest #GPUs. It now supports all #NVIDIA architectures from V100 onwards, bringing major speedups to more users. 🤗github.com/InternLM/lmdep…
Bonus Infra Stack (Infra teams love this): – Ollama: Local launcher with quant baked in – vLLM: API-compatible & batch-optimized – LMDeploy: Custom GPU serving – Llama.cpp: Great for mobile/edge Mix and match depending on your infra. #AIInfra2025 #Ollama #LMDeploy
💡 Transform your LLM into a high-performing AI with #LMDeploy! 🔧 TurboMind: Speed with C++ & CUDA 🎨 PyTorch: Flexible, developer-friendly 🌐 REST APIs + CLI: Effortless integration From setup to advanced techniques, explore it all: medium.com/@omkamal/unlea… #AI #LLM #LLMOps
#LMDeploy provides an OpenAI-compatible server, which means that it can be integrated into applications that use the OpenAI API. This makes it easy to switch from using OpenAI's services to running your own models on more affordable compute. vast.ai/article/servin…
🥳#LMDeploy support Llama3.1 and its Tool Calling. An example of calling "Wolfram Alpha" to perform complex mathematical calculations can be found from here. github.com/InternLM/lmdep… 😉Welcome to star LMDeploy! github.com/InternLM/lmdep… #LLaMA3 @AIatMeta @Meta
🚀 Big news in #lmdeploy v0.3.0! We've optimized GQA inference, achieving 24+ RPS for #internlm2-7b & 17+ for internlm2-20b—1.8x faster than #vLLM! 🌟 Also, introducing support for #Qwen 1.5-MOE, #DBRX, & #DeepSeek-VL. 🥰Stay tuned for more! github.com/InternLM/lmdep…
🥳Thrilled to announce LMDeploy v0.1.0 is here! The inference now achieves ~900 request/s for llama-7b. 🤗A100 benchmarks link: github.com/InternLM/lmdep… 🤗GitHub link: github.com/InternLM/lmdep… #LMDeploy
github.com
Release LMDeploy Release V0.1.0 · InternLM/lmdeploy
What's Changed 🚀 Features Add extra_requires to reduce dependencies by @RunningLeon in #580 TurboMind 2 by @lzhangzz in #590 Support loading hf model directly by @irexyc in #685 convert model ...
#lmdeploy #C++ LMDeploy is a toolkit for compressing, deploying, and serving LLMs. gtrending.top/content/3455/
🥳#LMDeploy v0.0.8 has arrived with two incredible features: ✅ Access to all capabilities of #CodeLlama - including code completion, infilling, instruct / chat, and python specialist ✅ Support for both #Baichuan2-7B-Base and Baichuan2-7B-Chat 👉github.com/InternLM/lmdep…
🥳Say hello to the new face of lmdeploy! We hope you love it as much as we do! #lmdeploy 🤗github.com/InternLM/lmdep…
🥳#lmdeploy Release v0.0.7! ✅Flash attention 2 is now supported, boosting context decoding speed by approximately 45% ✅Token_id decoding has been optimized for better efficiency ✅The gemm-tunned script has been packed in the PyPI package 🤗github.com/InternLM/lmdep…
github.com
Release LMDeploy Release V0.0.7 · InternLM/lmdeploy
Highlights Flash attention 2 is supported, boosting context decoding speed by approximately 45% Token_id decoding has been optimized for better efficiency The gemm-tunned script has been packed in...
🥰#lmdeploy v0.0.6 is now live! #LLM #AI ✅#Qwen-7B support with dynamic NTK scaling and logN scaling in turbomind ✅Tensor parallelism for W4A16 ✅Added an #OpenAI-like RESTful API ✅#Llama-2 70B 4-bit quantization 🥳Stay tuned for more exciting updates! github.com/InternLM/lmdep…
🥳An OpenAI-like RESTful API has been integrated to #LMDeploy. #LLMInference #RESTful-API #LLM 👉github.com/InternLM/lmdep… 🤗A Quick guide can be found from github.com/InternLM/lmdep…
🥳Significant update in #LMDeploy. #LLMInference 🤗Building on previous work of 4-bit quantized #LLM model inference, we've now added support for tensor parallelism 🤗Support Qwen-7B and Qwen-Chat-7B with dynamic NTK-RoPE scaling and dynamic logN scaling github.com/InternLM/lmdep…
🥳I just published Faster and More Efficient 4-bit quantized #LLM Model Inference. #LMDeploy 👉link.medium.com/rYLTnqEIiCb
link.medium.com
Faster and More Efficient 4-bit quantized LLM Model Inference
LMDeploy has released an exciting new feature — 4-bit quantization and inference. This not only trims down the model’s memory overhead to…
🥳#LMDeploy supports 4-bit quantized #LLM model inference, 2.4x faster than FP16 on #NVIDIA Geforce RTX 4090, which is the fastest open-source implementation as far as we know. 🤗Check this guide out for more detailed deployment information: github.com/InternLM/lmdep…
🥳#LMDeploy supports 4-bit quantized #LLM model inference, 2.4x faster than FP16 on #NVIDIA Geforce RTX 4090, which is the fastest open-source implementation as far as we know. 🤗Check this guide out for more detailed deployment information: github.com/InternLM/lmdep…
🥳Excited to announce that #OpenCompass is compatible with #LMDeploy 🤗Support Qwen-7B and XVERSE-13B ! Go to our leaderboard for more results! 😍(Preview) The feature of comparing models will soon be available on our platform. Stay tuned for more updates! github.com/InternLM/openc…
🧐Want to quickly deploy the #Llama2 models? 😍This article shows us how to quickly deploy the #Llama-2 models with #LMDeploy. 👉Let's get started! #LLM @MetaAI link.medium.com/Kv6YU3E8WBb
link.medium.com
Deploy Llama-2 models easily with LMDeploy!
This article will guide you on how to quickly deploy the Llama-2 models with LMDeploy.
🚀 Big news for #lmdeploy v0.10.1! 🥳Our #FP8 high-performance inference is no longer limited to the latest #GPUs. It now supports all #NVIDIA architectures from V100 onwards, bringing major speedups to more users. 🤗github.com/InternLM/lmdep…
🚀 Big news in #lmdeploy v0.3.0! We've optimized GQA inference, achieving 24+ RPS for #internlm2-7b & 17+ for internlm2-20b—1.8x faster than #vLLM! 🌟 Also, introducing support for #Qwen 1.5-MOE, #DBRX, & #DeepSeek-VL. 🥰Stay tuned for more! github.com/InternLM/lmdep…
🥳Say hello to the new face of lmdeploy! We hope you love it as much as we do! #lmdeploy 🤗github.com/InternLM/lmdep…
🥳Excited to announce that #OpenCompass is compatible with #LMDeploy 🤗Support Qwen-7B and XVERSE-13B ! Go to our leaderboard for more results! 😍(Preview) The feature of comparing models will soon be available on our platform. Stay tuned for more updates! github.com/InternLM/openc…
🥳#LMDeploy supports 4-bit quantized #LLM model inference, 2.4x faster than FP16 on #NVIDIA Geforce RTX 4090, which is the fastest open-source implementation as far as we know. 🤗Check this guide out for more detailed deployment information: github.com/InternLM/lmdep…
💡 Transform your LLM into a high-performing AI with #LMDeploy! 🔧 TurboMind: Speed with C++ & CUDA 🎨 PyTorch: Flexible, developer-friendly 🌐 REST APIs + CLI: Effortless integration From setup to advanced techniques, explore it all: medium.com/@omkamal/unlea… #AI #LLM #LLMOps
🥳#LMDeploy v0.0.8 has arrived with two incredible features: ✅ Access to all capabilities of #CodeLlama - including code completion, infilling, instruct / chat, and python specialist ✅ Support for both #Baichuan2-7B-Base and Baichuan2-7B-Chat 👉github.com/InternLM/lmdep…
Something went wrong.
Something went wrong.
United States Trends
- 1. Justin Fields 9,150 posts
- 2. Jets 65.6K posts
- 3. Patriots 141K posts
- 4. Drake Maye 18.3K posts
- 5. Henderson 20.8K posts
- 6. Jalen Johnson 4,513 posts
- 7. AD Mitchell 2,257 posts
- 8. Judge 177K posts
- 9. Pats 13.8K posts
- 10. Diggs 9,812 posts
- 11. Cal Raleigh 7,236 posts
- 12. Santana 13.4K posts
- 13. #TNFonPrime 3,198 posts
- 14. #criticalrolespoilers 2,111 posts
- 15. #GreysAnatomy 2,029 posts
- 16. Mike Vrabel 5,728 posts
- 17. Purdue 8,878 posts
- 18. #TNAiMPACT 5,643 posts
- 19. Metchie 1,305 posts
- 20. Tyrod N/A