Marketplace · 120+ models
NLP & Language Language at production scale
Text generation, translation, sentiment analysis, summarization, embeddings, and named entity recognition pipelines — from 1B chatbots to 70B reasoning models.
Editor's pick
The nlp & language model most teams reach for first.
Llama 3.1 70B Instruct
Open-weights chat model; strong general reasoning and tool use.
Spec sheet
- Family
- Meta
- Parameters
- 70B
- License
- Llama 3.1 Community
- Status
- Live
- Best for
- Language at production scale
- Sits in
- NLP & Language
Pricing and routing rank visible on InferenceBench. Variants and quantisations appear in the Yobibyte deploy console.
The rest of the lineup
5 more in NLP & Language. All deployable in one click.
Multilingual chat with 128K context and strong code performance.
High-quality reasoning, strong on multilingual and code workloads.
Lightweight sentence embeddings; the default for fast semantic search.
Showing 6 of 120+. The full catalog (with quantisations, hardware variants, and per-region pricing) lives in the Yobibyte console.
Quick start
Five lines to your first nlp & language call.
Every model in this category is reachable from the same Yobitel SDK. Swap the model name; the rest of the call shape stays identical. Authenticated via your workspace key.
from yobitel import Inference
# Llama 3.1 70B Instruct — open-weights chat
client = Inference(model="meta/llama-3.1-70b-instruct")
response = client.chat([
{"role": "system", "content": "You answer in three bullets."},
{"role": "user", "content": "Summarise the FinOps FOCUS spec."},
])
print(response.text)
print("tokens used:", response.usage.total_tokens)Where teams ship this
Real nlp & language. In production.
Four use cases that customers run today. Pick a model from the lineup above, deploy on Yobibyte, plug it into the surrounding stack. Done.
- 01
Customer support chatbots and copilots
- 02
Enterprise search and RAG over documents
- 03
Multilingual translation and localization
- 04
Document summarization at scale
Frameworks
Bring what your team already knows
Yobitel handles the serving layer (GPU scheduling, KV cache, autoscaling, request batching) so your team focuses on the model and the product.
Learn about YobibyteExplore the rest
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Related Yobitel services
The teams behind NLP & Language
Marketplace listings are the model layer. When the work needs labelled data, evaluation harnesses, production serving, or end-to-end pipelines, these are the Yobitel services teams that build them.
Yobitel service
Instruction tuning
Human-authored instruction + response pairs for SFT on open-weights LLMs.
Open serviceYobitel service
Preference / RLHF / DPO
Pairwise preferences and ranked outputs for RLHF and DPO alignment passes.
Open serviceYobitel service
Eval sets
Held-out gold sets for capability, regression, and red-team evals.
Open serviceYobitel service
AI inference
Production LLM serving with streaming, batching, and rolling deploys.
Open serviceDon't see what you need?
Bring your own model or fine-tune one of ours. Yobitel engineers can sit with your team and ship the right stack.