1.
OpenChat 3.5
OpenChat is a library of open-source language models, fine-tuned with "C-RLFT (Conditioned Reinforcement Learning Fine-Tuning)" - a strategy inspired by offline reinforcement learning. It has been trained on mixed-quality data without preference labels. • 8192 context
29.6M tokens
new
2.
Psyfighter 13B
A #merge model based on [Llama-2-13B](/models/meta-llama/llama-2-13b-chat) and made possible thanks to the compute provided by the KoboldAI community. It's a merge between:
- [KoboldAI/LLaMA2-13B-Tiefighter](https://huggingface.co/KoboldAI/LLaMA2-13B-Tiefighter)
- [chaoyi-wu/MedLLaMA_13B](https://huggingface.co/chaoyi-wu/MedLLaMA_13B)
- [Doctor-Shotgun/llama-2-13b-chat-limarp-v2-merged](https://huggingface.co/Doctor-Shotgun/llama-2-13b-chat-limarp-v2-merged).
#merge • 4096 context
3.9M tokens
new
3.
Anthropic: Claude v1
Anthropic's model for low-latency, high throughput text generation. Supports up to 100k tokens in one pass, or hundreds of pages of text. • 9000 context
2.1M tokens
3286%
4.
Anthropic: Claude 100k v1
Anthropic's model for low-latency, high throughput text generation. Supports up to 100k tokens in one pass, or hundreds of pages of text. • 100000 context
19.2M tokens
1730%
5.
OpenHermes 2.5 Mistral 7B
A continuation of [OpenHermes 2 model](/models/teknium/openhermes-2-mistral-7b), trained on additional code datasets.
Potentially the most interesting finding from training on a good ratio (est. of around 7-14% of the total dataset) of code instruction was that it has boosted several non-code benchmarks, including TruthfulQA, AGIEval, and GPT4All suite. It did however reduce BigBench benchmark score, but the net gain overall is significant. • 4096 context
225.4M tokens
694%
6.
OpenAI: GPT-3.5 Turbo 16k
This model offers four times the context length of gpt-3.5-turbo, allowing it to support approximately 20 pages of text in a single request at a higher cost. Training data: up to Sep 2021. • 16385 context
32.3M tokens
344%
7.
OpenAI: GPT-3.5 Turbo Instruct
This model is a variant of GPT-3.5 Turbo tuned for instructional prompts and omitting chat-related optimizations. Training data: up to Sep 2021. • 4095 context
4.7M tokens
322%
8.
MythoMist 7B
From the creator of [MythoMax](/models/gryphe/mythomax-l2-13b), merges a suite of models to reduce word anticipation, ministrations, and other undesirable words in ChatGPT roleplaying data.
It combines [Neural Chat 7B](/models/intel/neural-chat-7b), Airoboros 7b, [Toppy M 7B](/models/undi95/toppy-m-7b), [Zepher 7b beta](/models/huggingfaceh4/zephyr-7b-beta), [Nous Capybara 34B](/models/nousresearch/nous-capybara-34b), [OpenHeremes 2.5](/models/teknium/openhermes-2.5-mistral-7b), and many others.
#merge • 32768 context
57.6M tokens
242%
9.
OpenAI: GPT-3.5 Turbo 16k (preview)
The latest GPT-3.5 Turbo model with improved instruction following, JSON mode, reproducible outputs, parallel function calling, and more. Training data: up to Sep 2021. • 16385 context
17.7M tokens
200%
10.
OpenAI: GPT-4 Vision (preview)
Ability to understand images, in addition to all other [GPT-4 Turbo capabilties](/models/openai/gpt-4-1106-preview). Training data: up to Apr 2023.
**Note:** heavily rate limited by OpenAI while in preview. • 128000 context
2.6M tokens
187%
11.
OpenAI: Davinci 2
An InstructGPT model derived from the code-davinci-002 model, designed to follow instructions in prompts to provide detailed responses. Training data: up to Sep 2021. • 4095 context
17.4K tokens
163%
12.
Noromaid 20B
A collab between IkariDev and Undi. This merge is suitable for RP, ERP, and general knowledge.
#merge • 8192 context
18.9M tokens
155%
13.
Google: PaLM 2 Code Chat
PaLM 2 fine-tuned for chatbot conversations that help with code-related questions. • 7168 context
2.0M tokens
150%
14.
Anthropic: Claude Instant 100k v1
Anthropic's model for low-latency, high throughput text generation. Supports up to 100k tokens in one pass, or hundreds of pages of text. • 100000 context
1.0M tokens
140%
15.
Synthia 70B
SynthIA (Synthetic Intelligent Agent) is a LLama-2 70B model trained on Orca style datasets. It has been fine-tuned for instruction following as well as having long-form conversations. • 8192 context
4.3M tokens
86%
16.
Nous: Capybara 34B
This model is trained on the Yi-34B model for 3 epochs on the Capybara dataset. It's the first 34B Nous model and first 200K context length Nous model.
**Note:** This endpoint currently supports 32k context. • 32000 context
3.0M tokens
82%
17.
Anthropic: Claude Instant v1
Anthropic's model for low-latency, high throughput text generation. Supports up to 100k tokens in one pass, or hundreds of pages of text. • 100000 context
59.4M tokens
79%
18.
OpenAI: GPT-4
OpenAI's flagship model, GPT-4 is a large-scale multimodal language model capable of solving difficult problems with greater accuracy than previous models due to its broader general knowledge and advanced reasoning capabilities. Training data: up to Sep 2021. • 8191 context
56.4M tokens
48%
19.
OpenAI: GPT-3.5 Turbo
GPT-3.5 Turbo is OpenAI's fastest model. It can understand and generate natural language or code, and is optimized for chat and traditional completion tasks. Training data: up to Sep 2021. • 4095 context
95.3M tokens
45%
20.
Toppy M 7B
A wild 7B parameter model that merges several models using the new task_arithmetic merge method from mergekit.
List of merged models:
- NousResearch/Nous-Capybara-7B-V1.9
- [HuggingFaceH4/zephyr-7b-beta](/models/huggingfaceh4/zephyr-7b-beta)
- lemonilia/AshhLimaRP-Mistral-7B
- Vulkane/120-Days-of-Sodom-LoRA-Mistral-7b
- Undi95/Mistral-pippa-sharegpt-7b-qlora
#merge • 32768 context
1.3B tokens
41%