Transformers
PyTorch
Safetensors
GGUF
Bengali
mistral
text-generation-inference
unsloth
trl
sft
8-bit precision
Instructions to use barunsaha/misti with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use barunsaha/misti with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("barunsaha/misti", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use barunsaha/misti 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 barunsaha/misti:Q4_K_M # Run inference directly in the terminal: llama cli -hf barunsaha/misti:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf barunsaha/misti:Q4_K_M # Run inference directly in the terminal: llama cli -hf barunsaha/misti:Q4_K_M
Use 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 barunsaha/misti:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf barunsaha/misti:Q4_K_M
Build 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 barunsaha/misti:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf barunsaha/misti:Q4_K_M
Use Docker
docker model run hf.co/barunsaha/misti:Q4_K_M
- Llama new
- LM Studio
- Jan
- Ollama
How to use barunsaha/misti with Ollama:
ollama run hf.co/barunsaha/misti:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use barunsaha/misti with Docker Model Runner:
docker model run hf.co/barunsaha/misti:Q4_K_M
- Lemonade
How to use barunsaha/misti with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull barunsaha/misti:Q4_K_M
Run and chat with the model
lemonade run user.misti-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Trained with Unsloth
Browse files- config.json +27 -2
- pytorch_model-00001-of-00003.bin +1 -1
- pytorch_model-00002-of-00003.bin +1 -1
- pytorch_model-00003-of-00003.bin +1 -1
config.json
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{
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"_name_or_path": "unsloth/mistral-7b-bnb-4bit",
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"architectures": [
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"MistralForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 14336,
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"max_position_embeddings": 32768,
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"model_type": "mistral",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"pad_token_id": 2,
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"rms_norm_eps": 1e-05,
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"rope_theta": 10000.0,
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"sliding_window": 4096,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.39.3",
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"unsloth_version": "2024.4",
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"use_cache": true,
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"vocab_size": 32000
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}
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pytorch_model-00001-of-00003.bin
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