GGUF
Merge
mergekit
lazymergekit
bardsai/jaskier-7b-dpo-v3.3
CultriX/NeuralTrix-v4-bf16
CultriX/NeuralTrix-7B-dpo
How to use from
llama.cppInstall from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf CultriX/NeuralTrix-bf16-GGUF:Q6_K# Run inference directly in the terminal:
llama cli -hf CultriX/NeuralTrix-bf16-GGUF:Q6_KUse pre-built binary
# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf CultriX/NeuralTrix-bf16-GGUF:Q6_K# Run inference directly in the terminal:
./llama-cli -hf CultriX/NeuralTrix-bf16-GGUF:Q6_KBuild from source code
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf CultriX/NeuralTrix-bf16-GGUF:Q6_K# Run inference directly in the terminal:
./build/bin/llama-cli -hf CultriX/NeuralTrix-bf16-GGUF:Q6_KUse Docker
docker model run hf.co/CultriX/NeuralTrix-bf16-GGUF:Q6_KQuick Links
Note: This is a test to check if it fixed the INSTINSTINST error in the output! Please let me know if you still get errors using this model.
NeuralTrix-bf16
NeuralTrix-bf16 is a merge of the following models using LazyMergekit:
🧩 Configuration
models:
- model: eren23/dpo-binarized-NeuralTrix-7B
# no parameters necessary for base model
- model: bardsai/jaskier-7b-dpo-v3.3
parameters:
density: 0.65
weight: 0.4
- model: CultriX/NeuralTrix-v4-bf16
parameters:
density: 0.6
weight: 0.35
- model: CultriX/NeuralTrix-7B-dpo
parameters:
density: 0.6
weight: 0.35
merge_method: dare_ties
base_model: eren23/dpo-binarized-NeuralTrix-7B
parameters:
int8_mask: true
dtype: bfloat16
💻 Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "CultriX/"
messages = [{"role": "user", "content": "What is a large language model?"}]
tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
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Base model
CultriX/NeuralTrix-7B-dpo
Install (macOS, Linux)
# Start a local OpenAI-compatible server with a web UI: llama serve -hf CultriX/NeuralTrix-bf16-GGUF:Q6_K# Run inference directly in the terminal: llama cli -hf CultriX/NeuralTrix-bf16-GGUF:Q6_K