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mattshumer/Reflection-Llama-3.1-70B cover image
bfloat16
8k
Replaced
  • text-generation

Reflection Llama-3.1 70B is trained with a new technique called Reflection-Tuning that teaches a LLM to detect mistakes in its reasoning and correct course. The model was trained on synthetic data.

meta-llama/Llama-2-13b-chat-hf cover image
fp16
4k
Replaced
  • text-generation

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.

meta-llama/Llama-2-70b-chat-hf cover image
fp16
4k
Replaced
  • text-generation

LLaMa 2 is a collections of LLMs trained by Meta. This is the 70B chat optimized version. This endpoint has per token pricing.

meta-llama/Llama-2-7b-chat-hf cover image
fp16
4k
Replaced
  • text-generation

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.

microsoft/Phi-3-medium-4k-instruct cover image
bfloat16
4k
Replaced
  • text-generation

The Phi-3-Medium-4K-Instruct is a powerful and lightweight language model with 14 billion parameters, trained on high-quality data to excel in instruction following and safety measures. It demonstrates exceptional performance across benchmarks, including common sense, language understanding, and logical reasoning, outperforming models of similar size.

mistralai/Mistral-7B-Instruct-v0.1 cover image
fp16
32k
Replaced
  • text-generation

The Mistral-7B-Instruct-v0.1 Large Language Model (LLM) is a instruct fine-tuned version of the Mistral-7B-v0.1 generative text model using a variety of publicly available conversation datasets.

mistralai/Mistral-7B-Instruct-v0.2 cover image
fp16
32k
Replaced
  • text-generation

The Mistral-7B-Instruct-v0.2 Large Language Model (LLM) is a instruct fine-tuned version of the Mistral-7B-v0.2 generative text model using a variety of publicly available conversation datasets.

mistralai/Mixtral-8x22B-Instruct-v0.1 cover image
bfloat16
64k
Replaced
  • text-generation

This is the instruction fine-tuned version of Mixtral-8x22B - the latest and largest mixture of experts large language model (LLM) from Mistral AI. This state of the art machine learning model uses a mixture 8 of experts (MoE) 22b models. During inference 2 experts are selected. This architecture allows large models to be fast and cheap at inference.

mistralai/Mixtral-8x22B-v0.1 cover image
fp16
64k
Replaced
  • text-generation

Mixtral-8x22B is the latest and largest mixture of expert large language model (LLM) from Mistral AI. This is state of the art machine learning model using a mixture 8 of experts (MoE) 22b models. During inference 2 expers are selected. This architecture allows large models to be fast and cheap at inference. This model is not instruction tuned.

nvidia/Nemotron-4-340B-Instruct cover image
bfloat16
4k
Replaced
  • text-generation

Nemotron-4-340B-Instruct is a chat model intended for use for the English language, designed for Synthetic Data Generation

openai/clip-vit-base-patch32 cover image
$0.0005 / sec
  • zero-shot-image-classification

The CLIP model was developed by OpenAI to investigate the robustness of computer vision models. It uses a Vision Transformer architecture and was trained on a large dataset of image-caption pairs. The model shows promise in various computer vision tasks but also has limitations, including difficulties with fine-grained classification and potential biases in certain applications.

openai/clip-vit-large-patch14-336 cover image
$0.0005 / sec
  • zero-shot-image-classification

A zero-shot-image-classification model released by OpenAI. The clip-vit-large-patch14-336 model was trained from scratch on an unknown dataset and achieves unspecified results on the evaluation set. The model's intended uses and limitations, as well as its training and evaluation data, are not provided. The training procedure used an unknown optimizer and precision, and the framework versions included Transformers 4.21.3, TensorFlow 2.8.2, and Tokenizers 0.12.1.

openai/whisper-base cover image
Replaced
  • automatic-speech-recognition

Whisper is a pre-trained model for automatic speech recognition (ASR) and speech translation. It was trained on 680k hours of labelled data and demonstrates a strong ability to generalize to many datasets and domains without fine-tuning. The model is based on a Transformer encoder-decoder architecture. Whisper models are available for various languages including English, Spanish, French, German, Italian, Portuguese, Russian, Chinese, Japanese, Korean, and many more.

openai/whisper-base.en cover image
Replaced
  • automatic-speech-recognition

Whisper is a pre-trained model for automatic speech recognition (ASR) and speech translation. It was trained on 680k hours of labelled data and demonstrated a strong ability to generalise to many datasets and domains without fine-tuning. Whisper checks pens are available in five configurations of varying model sizes, including a smallest configuration trained on English-only data and a largest configuration trained on multilingual data. This one is English-only.

openai/whisper-large cover image
Replaced
  • automatic-speech-recognition

Whisper is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multi-task model that can perform multilingual speech recognition as well as speech translation and language identification.

openai/whisper-medium cover image
Replaced
  • automatic-speech-recognition

Whisper is a pre-trained model for automatic speech recognition (ASR) and speech translation. It was trained on 680k hours of labeled data and demonstrates strong abilities to generalize to various datasets and domains without fine-tuning. The model is based on a Transformer encoder-decoder architecture.

openai/whisper-medium.en cover image
Replaced
  • automatic-speech-recognition

Whisper is a pre-trained model for automatic speech recognition (ASR) and speech translation. Trained on 680k hours of labelled data, Whisper models demonstrate a strong ability to generalise to many datasets and domains without fine-tuning. The primary intended users of these models are AI researchers studying robustness, generalisation, and capabilities of the current model.

openai/whisper-small cover image
Replaced
  • automatic-speech-recognition

Whisper is a pre-trained model for automatic speech recognition (ASR) and speech translation. It was trained on 680k hours of labelled data and demonstrates a strong ability to generalize to many datasets and domains without the need for fine-tuning. The model is based on a Transformer architecture and uses a large-scale weak supervision technique.