Text Generation
Transformers
Safetensors
GGUF
English
bitnet
bitnet-b1.58
ternary
cpu
tinydialogues
conversational
Instructions to use zerolimites/BitNet-TinyDialogues-1.58b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zerolimites/BitNet-TinyDialogues-1.58b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="zerolimites/BitNet-TinyDialogues-1.58b") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("zerolimites/BitNet-TinyDialogues-1.58b") model = AutoModelForCausalLM.from_pretrained("zerolimites/BitNet-TinyDialogues-1.58b", device_map="auto") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=256) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use zerolimites/BitNet-TinyDialogues-1.58b with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf zerolimites/BitNet-TinyDialogues-1.58b:TQ1_0 # Run inference directly in the terminal: llama cli -hf zerolimites/BitNet-TinyDialogues-1.58b:TQ1_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf zerolimites/BitNet-TinyDialogues-1.58b:TQ1_0 # Run inference directly in the terminal: llama cli -hf zerolimites/BitNet-TinyDialogues-1.58b:TQ1_0
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf zerolimites/BitNet-TinyDialogues-1.58b:TQ1_0 # Run inference directly in the terminal: ./build/bin/llama cli -hf zerolimites/BitNet-TinyDialogues-1.58b:TQ1_0
Use Docker
docker model run hf.co/zerolimites/BitNet-TinyDialogues-1.58b:TQ1_0
- Llama new
- LM Studio
- Jan
- vLLM
How to use zerolimites/BitNet-TinyDialogues-1.58b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "zerolimites/BitNet-TinyDialogues-1.58b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "zerolimites/BitNet-TinyDialogues-1.58b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/zerolimites/BitNet-TinyDialogues-1.58b:TQ1_0
- SGLang
How to use zerolimites/BitNet-TinyDialogues-1.58b with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "zerolimites/BitNet-TinyDialogues-1.58b" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "zerolimites/BitNet-TinyDialogues-1.58b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "zerolimites/BitNet-TinyDialogues-1.58b" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "zerolimites/BitNet-TinyDialogues-1.58b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Ollama
How to use zerolimites/BitNet-TinyDialogues-1.58b with Ollama:
ollama run hf.co/zerolimites/BitNet-TinyDialogues-1.58b:TQ1_0
- Unsloth Desktop
- Docker Model Runner
How to use zerolimites/BitNet-TinyDialogues-1.58b with Docker Model Runner:
docker model run hf.co/zerolimites/BitNet-TinyDialogues-1.58b:TQ1_0
- Lemonade
How to use zerolimites/BitNet-TinyDialogues-1.58b with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull zerolimites/BitNet-TinyDialogues-1.58b:TQ1_0
Run and chat with the model
lemonade run user.BitNet-TinyDialogues-1.58b-TQ1_0
List all available models
lemonade list
- Atomic Chat
File size: 1,023 Bytes
655f931 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 | # Validação
## GGUF
- Conversão: `convert_hf_to_gguf.py` (llama.cpp commit `3de52ac38818978d6da8f386eda43a856e53714a`) + patch BitNet.
- Quantização: `llama-quantize` `TQ1_0` e `TQ2_0`, embeddings `Q8_0`.
- Runtime: `llama-cli`/`llama-server` com FFN `LLM_FFN_RELU_SQR`.
## Tokenização
`llama-tokenize` e `LlamaTokenizer` produzem os mesmos IDs para:
```text
user: can we play? assistant:
[290, 1951, 315, 306, 399, 1958, 289, 1951]
```
## Geração greedy (temp 0)
Prompt: `user: can we play? assistant:`
- F32: `yes, but we need to clean up. we need to clean up.`
- TQ1_0: `yes, but we need to clean up. we need to clean up.`
- TQ2_0: `yes, but we need to clean up. we need to clean up.`
## SHA256
```text
bitnet-tinydialogues-TQ1_0.gguf 222a077dc66fda965da7d0172c918fc2151856c9d0697bf6ee9a2705f2648e28
bitnet-tinydialogues-TQ2_0.gguf 53b4f43754113fcad1078eea4b57b72bb00776d1535f67f39be7b1de4d184249
bitnet-tinydialogues-f32.gguf d0ec7cec16a986fc883756d5ddb9dd433280ed8cbe69fda3725117b23463794a
```
|