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How to use Yukang/Llama-2-7b-longlora-32k with Transformers: # Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text ...

c_attachment_tables.md — table 1: the 12 text-only prompts and each arm's reply; table 2: files and environment; table 3: delegation lines. x12_prompts.json — the 12 prompts (a passage about a living ...

How to use Launch80/Qwopus3.8-27B-Coder-Flash-Int4-baked with Transformers: # Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline ...

# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "azampatti/Qwen3.8-Flash-Next-125B-A5B-INT4-AutoRound" # Call the server using curl ...

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How to use nytopop/Qwen3-14B-abliterated.w8a8 with Transformers: # Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text ...

How to use ToPo-ToPo/Ornith-1.5-122B-mlx-4bit with MLX: # Make sure mlx-vlm is installed # pip install --upgrade mlx-vlm from mlx_vlm import load, generate from mlx_vlm.prompt_utils import ...

Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.

How to use llmfan46/Qwen3.5-9B-Ultra-Uncensored-Heretic-GGUF with Transformers: # Use a pipeline as a high-level helper from transformers import pipeline pipe ...

import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Qwen/Qwen-Image-2.1", dtype=torch ...

Tiny causal transformers with d_model values 8, 16, 32, 64, 1 seed(s) per width, vocabulary size 4096, context length 256, and a nominal schedule of 1,999,998,976 training tokens. Actual per-model ...