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JC1DA
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JC1DA
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| Parameter | Value |
|---|---|
| Method | AutoRound v0.12.3 |
| Scheme | W4A16 (4-bit int weights, 16-bit fp activations) |
| Group Size | 128 |
| Symmetric | Yes |
| Packing Format | auto_round:auto_gptq (GPTQ compatible) |
| Dataset | NeelNanda/pile-10k |
| Calibration Samples | 256 |
| Sequence Length | 4096 |
| Iterations | 512 |
| Seed | 42 |
linear_attn.in_proj_a and linear_attn.in_proj_b (all layers)embed_tokensvisual.* layersmtp.* (multi-token prediction) layerslm_headpython
from transformers import AutoModelForCausalLM, AutoTokenizer model = AutoModelForCausalLM.from_pretrained( "DavidAU_Qwen3.8-27B-TURBO-Fable-Cold-Fusion-735-882-Heretic-Uncensored-NM-DAU-W4A16", device_map="auto", torch_dtype="auto")tokenizer = AutoTokenizer.from_pretrained( "DavidAU_Qwen3.8-27B-TURBO-Fable-Cold-Fusion-735-882-Heretic-Uncensored-NM-DAU-W4A16") messages = [ {"role": "user", "content": "Write a short poem about quantum entanglement."}]prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)inputs = tokenizer(prompt, return_tensors="pt").to(model.device) outputs = model.generate(**inputs, max_new_tokens=512, temperature=0.7, top_p=0.95)print(tokenizer.decode(outputs[0][inputs.input_ids.shape[1]:], skip_special_tokens=True))The model is GPTQ-compatible. Convert to GGUF for llama.cpp inference:
bash
python convert_hf_to_gguf.py . --outtype q4_K_M| VRAM | Notes |
|---|---|
| ~14 GB | Minimum with KV cache optimization |
| 16 GB | Comfortable for most use cases |
| 24 GB+ | Full context, longer generations |
Recommended settings from generation_config.json:
Apache-2.0
bibtex
@misc{davidau2025qwen38, title={DavidAU_Qwen3.8-27B-TURBO-Fable-Cold-Fusion-735-882-Heretic-Uncensored-NM-DAU}, author={DavidAU}, year={2025}, howpublished={\url{https://huggingface.co/DavidAU_Qwen3.8-27B-TURBO-Fable-Cold-Fusion-735-882-Heretic-Uncensored-NM-DAU}}}from transformers import AutoModelForCausalLM, AutoTokenizer model = AutoModelForCausalLM.from_pretrained( "DavidAU_Qwen3.8-27B-TURBO-Fable-Cold-Fusion-735-882-Heretic-Uncensored-NM-DAU-W4A16", device_map="auto", torch_dtype="auto")tokenizer = AutoTokenizer.from_pretrained( "DavidAU_Qwen3.8-27B-TURBO-Fable-Cold-Fusion-735-882-Heretic-Uncensored-NM-DAU-W4A16") messages = [ {"role": "user", "content": "Write a short poem about quantum entanglement."}]prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)inputs = tokenizer(prompt, return_tensors="pt").to(model.device) outputs = model.generate(**inputs, max_new_tokens=512, temperature=0.7, top_p=0.95)print(tokenizer.decode(outputs[0][inputs.input_ids.shape[1]:], skip_special_tokens=True))@misc{davidau2025qwen38, title={DavidAU_Qwen3.8-27B-TURBO-Fable-Cold-Fusion-735-882-Heretic-Uncensored-NM-DAU}, author={DavidAU}, year={2025}, howpublished={\url{https://huggingface.co/DavidAU_Qwen3.8-27B-TURBO-Fable-Cold-Fusion-735-882-Heretic-Uncensored-NM-DAU}}}