OpenHermes 7B
OpenHermes 7B has model metadata, but missing tracked provider pricing keeps it from being a default production pick.
Use it for
- Teams evaluating general LLM work
- Workloads that can use a 32k context window
Do not use it for
- Cost-sensitive launches that need sourced token pricing
- Vision or document-understanding workloads
- Strict JSON or tool-calling flows
- Family
- OpenHermes
- Released
- 2023-07-18
- Context
- 32k
- Parameters
- 7B
- Architecture
- Decoder Only
- Specialization
- general
- Training
- finetuned
About
OpenHermes 7B is a notable large language model in natural language processing, recognized for fine-tuning on an open-source dataset and employing sample packing to expedite training. It is built on the Llama-2-7b-hf base and trained with around 242,000 entries, including GPT-4-generated content from open AI community datasets. It excludes certain private datasets, focusing on comprehensive sources like GPTeacher and WizardLM. The model's capabilities are evidenced by mixed performance on benchmarks like GPT-4All, BigBench, and TruthfulQA, indicating variable strengths across tasks. While not yet applicable for serverless API deployment, it supports dedicated Inference Endpoints 1.
OpenHermes 7B is a model in the OpenHermes family. The structured metadata tracks a 32k-token context window. No headline benchmark score is tracked for OpenHermes 7B yet.
Top use-case fit
No primary decision-task fit is mapped for this model yet.
Provider price ladder
No tracked provider token pricing is available for this model yet.
Capabilities
No model capability flags are currently sourced.
Benchmark peer barsfor Coding
No task-mapped benchmark peers are available for this model yet.
Migration checks
No linked migration route is available for this model yet.