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hifi-gan-template

idefics-9b-instruct-8bit

IDEFICS (Image-aware Decoder Enhanced à la Flamingo with Interleaved Cross-attentionS) is an open-access reproduction of Flamingo, a closed-source visual language model developed by Deepmind. Like GPT-4, the multimodal model accepts arbitrary sequences of image and text inputs and produces text outputs.

inferless-docker-import-examples

inferless_tutorials

jamba-v0.1

Jamba is a state-of-the-art, hybrid SSM-Transformer LLM. It delivers throughput gains over traditional Transformer-based models, while outperforming or matching the leading models of its size class on most common benchmarks.

jina-embeddings-v2

jina-embeddings-v2-base-en is an English, monolingual embedding model supporting 8192 sequence length. It is based on a BERT architecture (JinaBERT) that supports the symmetric bidirectional variant of ALiBi to allow longer sequence length. The backbone jina-bert-v2-base-en is pretrained on the C4 dataset.

llama-2-13b-chat-gptq

Llama 2 is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters. This is the 13B fine-tuned GPTQ quantized model, optimized for dialogue use cases.

llama-2-13b-hf

Llama 2 is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters. This is the repository for the 7B fine-tuned model, optimized for dialogue use cases and converted for the Hugging Face Transformers format. Links to other models can be found in the index at the bottom.

llama-2-13b-hf-a10g

Llama 2 is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters. This is the repository for the 13B fine-tuned model, optimized for dialogue use cases and converted for the Hugging Face Transformers format. Links to other models can be found in the index at the bottom.

llama-2-70b-chat-gptq

About Llama 2 is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters. This is the 70B fine-tuned GPTQ quantized model, optimized for dialogue use cases.

llama-2-7b-chat

Llama 2 7B Chat is the smallest chat model in the Llama 2 family of large language models developed by Meta AI. This model has 7 billion parameters and was pretrained on 2 trillion tokens of data from publicly available sources. It has been fine-tuned on over one million human-annotated instruction datasets

llama-2-7b-gptq

Llama 2 is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters. This is the repository for the 7B fine-tuned model, optimized for dialogue use cases and converted for the Hugging Face Transformers format. Links to other models can be found in the index at the bottom.

llama-2-7b-hf

Llama 2 is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters. This is the repository for the 13B fine-tuned model, optimized for dialogue use cases and converted for the Hugging Face Transformers format. Links to other models can be found in the index at the bottom.

llama-3

Llama 3 is an auto-regressive language model, leveraging a refined transformer architecture.It incorporate supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to ensure alignment with human preferences.

llama2-13b-hf-8bit

Llama 2 is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters. This is the repository for the 13B fine-tuned model, optimized for dialogue use cases and converted for the Hugging Face Transformers format. Links to other models can be found in the index at the bottom.

llama3-tenyxchat-70b

llava-1.5-13b

llava-1.6-34b

logo-generator

medcpt-article-encoder

MedCPT generates embeddings of biomedical texts that can be used for semantic search (dense retrieval). MedCPT Article Encoder: compute the embeddings of articles (e.g., PubMed titles & abstracts). In this template, we will import the MedCPT Article Encoder on the Inferless Platform.

medcpt-query-encoder

MedCPT generates embeddings of biomedical texts that can be used for semantic search (dense retrieval). MedCPT Query Encoder: compute the embeddings of short texts (e.g., questions, search queries, sentences). In this template, we will import the MedCPT Query Encoder on the Inferless Platform.

meditron-7b-gptq

Meditron is a suite of open-source medical Large Language Models (LLMs). Meditron-7B is a 7 billion parameters model adapted to the medical domain from Llama-2-7B through continued pretraining on a comprehensively curated medical corpus.

melotts

mistral-7b

The Mistral-7B-v0.1 Large Language Model (LLM) is a pretrained generative text model with 7 billion parameters. Mistral-7B-v0.1 outperforms Llama 2 13B on all benchmarks we tested.

mixral-8x7b

Mixtral is a large language model developed by Mistral AI, a French artificial intelligence company. It is a sparse Mixture of Experts (MoE) model with 8 experts per MLP, totaling 45 billion parameters. Mixtral is designed to handle contexts of up to 32,000 tokens.

mixtral-8x7b-v0.1

The Mixtral-8x7B Large Language Model (LLM) is a pretrained generative Sparse Mixture of Experts. The Mistral-8x7B outperforms Llama 2 70B on most benchmarks we tested.

mixtral-echo

Tryecho's Mixtral-echo is a adapter for Mixtral model. The Mixtral-8x7B Large Language Model (LLM) is a pretrained generative Sparse Mixture of Experts. The Mistral-8x7B outperforms Llama 2 70B on most benchmarks.

model-onnx-runtime

moondream1

Moondream1 is a 1.6B parameter model built using SigLIP, Phi-1.5 and the LLaVa training dataset.

moondream2

Moondream2 is a small vision language model designed to run efficiently on edge devices.