Get a weekly rundown of the latest AI models and research... subscribe! https://aimodels.substack.com/

Ethzanalytics

Rank:

Average Model Cost: $0.0000

Number of Runs: 3,383

Models by this creator

↗️

blip2-flan-t5-xl-sharded

Sharded BLIP-2 Model Card - flan-t5-xl This is a sharded version of the blip2-flan-t5-xl which leverages Flan T5-xl for image-to-text tasks such as image captioning and visual question answering. this model repo is sharded so it can be easily loaded on low-RAM Colab runtimes :) Refer to the original model card for more details about the model description, intended uses, and limitations, as well as instructions for how to use the model on CPU and GPU in different precisions. Usage Refer to the original model card for details or see this blog post. Here is how you can use it on CPU: Install Requires the current main of transformers (at time of writing): Use (this is for CPU, check out the original model card/blog for fp16 and int8 usage)

Read more

$-/run

2.1K

Huggingface

🔗

dolly-v2-12b-sharded-8bit

dolly-v2-12b: sharded 8bit checkpoint This is a sharded checkpoint (with ~4GB shards) of the databricks/dolly-v2-12b model in 8bit precision using bitsandbytes. Refer to the original model for all details w.r.t. to the model. For more info on loading 8bit models, refer to the example repo and/or the 4.28.0 release info. total model size is only ~12.5 GB! this enables low-RAM loading, i.e. Colab :) update: generation speed can be greatly improved by setting use_cache=True and generating via contrastive search. example notenook here Basic Usage install/upgrade transformers, accelerate, and bitsandbytes. For this to work you must have transformers>=4.28.0 and bitsandbytes>0.37.2. Load the model. As it is serialized in 8bit you don't need to do anything special:

Read more

$-/run

447

Huggingface

🎲

mpt-7b-storywriter-sharded

mpt-7b-storywriter: sharded This is a version of the mpt-7b-storywriter model, sharded to 2 GB chunks for low-RAM loading (i.e. Colab). The weights are stored in bfloat16 so in theory you can run this on CPU, though it may take forever. Please refer to the previously linked repo for details on usage/implementation/etc. This model was downloaded from the original repo under Apache-2.0 and is redistributed under the same license. Basic Usage Install/upgrade packages: Load the model: Then you can use model.generate() as you would normally - see the notebook for details.

Read more

$-/run

176

Huggingface

🏷️

dolly-v2-7b-sharded-8bit

dolly-v2-7b: 8-bit sharded checkpoint This is a sharded checkpoint (with ~2GB shards) of the databricks/dolly-v2-7b model in 8-bit precision using bitsandbytes. Refer to the original model for all details. For more info on loading 8bit models, refer to the example repo and/or the 4.28.0 release info. total model size is only ~7.5 GB! this enables low-RAM loading, i.e. Colab :) Basic Usage install/upgrade transformers, accelerate, and bitsandbytes. For this to work you must have transformers>=4.28.0 and bitsandbytes>0.37.2. Load the model. As it is serialized in 8bit you don't need to do anything special:

Read more

$-/run

158

Huggingface

🌀

stablelm-tuned-alpha-7b-sharded-8bit

This is a sharded checkpoint (with ~4GB shards) of the stabilityai/stablelm-tuned-alpha-7b model in 8bit precision using bitsandbytes. Refer to the original model for all details w.r.t. to the model. For more info on loading 8bit models, refer to the example repo and/or the 4.28.0 release info. You can use this model as a drop-in replacement in the notebook for the standard sharded models. Install/upgrade transformers, accelerate, and bitsandbytes. For this to work you must have transformers>=4.28.0 and bitsandbytes>0.37.2. Load the model. As it is serialized in 8bit you don't need to do anything special:

Read more

$-/run

144

Huggingface

🌀

stablelm-tuned-alpha-7b-sharded

StableLM-Tuned-Alpha 7b: sharded checkpoint This is a sharded checkpoint (with ~4GB shards) of the model. Refer to the original model for all details. this enables low-RAM loading, i.e. Colab :) Basic Usage install transformers, accelerate, and bitsandbytes. Load the model in 8bit, then run inference:

Read more

$-/run

143

Huggingface

🏷️

dolly-v2-7b-sharded

dolly-v2-7b: sharded checkpoint This is a sharded checkpoint (with ~4GB shards) of the databricks/dolly-v2-7b model. Refer to the original model for all details. this enables low-RAM loading, i.e. Colab :) Basic Usage install transformers, accelerate, and bitsandbytes. Load the model in 8bit, then run inference:

Read more

$-/run

64

Huggingface

🖼️

RedPajama-INCITE-Chat-3B-v1-GPTQ-4bit-128g

Platform did not provide a description for this model.

Read more

$-/run

52

Huggingface

🌐

stablelm-tuned-alpha-3b-gptq-4bit-128g

No description available.

Read more

$-/run

49

Huggingface

🛠️

ai-msgbot-gpt2-XL-dialogue

ai-msgbot: GPT2-XL-dialogue GPT2-XL (~1.5 B parameters) trained on the Wizard of Wikipedia dataset for 40k steps with 33/36 layers frozen using aitextgen. The resulting model was then further fine-tuned on the Daily Dialogues for 40k steps, with 34/36 layers frozen. Designed for use with ai-msgbot to create an open-ended chatbot (of course, if other use cases arise, have at it). conversation data The dataset was tokenized and fed to the model as a conversation between two speakers, whose names are below. This is relevant for writing prompts and filtering/extracting text from responses. script_speaker_name = person alpha script_responder_name = person beta examples the default inference API examples should work okay an ideal test would be explicitly adding person beta into the prompt text the model is forced to respond to instead of adding onto the entered prompt. citations

Read more

$-/run

40

Huggingface

Similar creators