Text / Altworld

Hemmingway 1

Hemmingway 1 is a text-generation model from the repository Altworld/Hemmingway-1, licensed under cc-by-nc-4.0. Its official model card describes it as built on Qwen/Qwen3.8-27B with 27B parameters, a 262,144-token context, and availability as safetensors weights through the transformers library. It is presented for English chat and creative-writing use, focusing on everyday messages and human-like tone. The card reports comparisons and benchmark placements but provides no hardware requirements or independent verification.

EstimatedRepository opened Sep 20, 2026Source checked 9/23/2026Version: b987f180
LOCALRENTED GPUOPEN WEIGHTS

At a glance

Parameters
26.90B
Architecture
qwen3_5_text
Context length
262,144
License
cc-by-nc-4.0
Software
vLLM, Transformers
View the model source
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Best for

  • Drafting everyday messages such as texts to a landlord, emails, and notes to colleagues
  • Assisting with money and administrative writing
  • Assisting with work-related writing
  • Composing hard asks or messages the user keeps rewriting
  • Assisting with persuasive writing or talking someone round

Tradeoffs

  • Licensed CC BY-NC 4.0, so commercial use requires a separate agreement
  • Model card lists only English language use
  • Stated to lose on hostile storytelling and long story turns relative to story models
  • Benchmark and comparison claims are from the model card and lack independent verification here
  • No hardware requirements, performance figures, or compatibility details are stated or inferred

Ways to run it

vLLM · Linux

Repository-specific command in publisher documentation; confirm dependencies and hardware in the source.

vllm serve Altworld/Hemmingway-1 --max-model-len 262144
Official instructions

Transformers · See official guide

Repository-specific command in publisher documentation; confirm dependencies and hardware in the source.

from transformers import AutoModelForCausalLM, AutoTokenizer model_id = "Altworld/Hemmingway-1" tok = AutoTokenizer.from_pretrained(model_id) model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto", dtype="auto") messages = [{"role": "user", "content": "Write the text I send my landlord about the broken boiler."}] ids = tok.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt").to(model.device) out = model.generate(ids, max_new_tokens=512) print(tok.decode(out[0][ids.shape[-1]:], skip_special_tokens=True))
Official instructions

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