Instructions to use Nameuser1/DeepSeek-Coder-V2-Lite-Instruct-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use Nameuser1/DeepSeek-Coder-V2-Lite-Instruct-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Nameuser1/DeepSeek-Coder-V2-Lite-Instruct-GGUF", filename="DeepSeek-Coder-V2-Lite-Instruct-Q5_K_M.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use Nameuser1/DeepSeek-Coder-V2-Lite-Instruct-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Nameuser1/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q5_K_M # Run inference directly in the terminal: llama-cli -hf Nameuser1/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q5_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Nameuser1/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q5_K_M # Run inference directly in the terminal: llama-cli -hf Nameuser1/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q5_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 Nameuser1/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q5_K_M # Run inference directly in the terminal: ./llama-cli -hf Nameuser1/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q5_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 Nameuser1/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q5_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Nameuser1/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q5_K_M
Use Docker
docker model run hf.co/Nameuser1/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q5_K_M
- LM Studio
- Jan
- Ollama
How to use Nameuser1/DeepSeek-Coder-V2-Lite-Instruct-GGUF with Ollama:
ollama run hf.co/Nameuser1/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q5_K_M
- Unsloth Studio new
How to use Nameuser1/DeepSeek-Coder-V2-Lite-Instruct-GGUF with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Nameuser1/DeepSeek-Coder-V2-Lite-Instruct-GGUF to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Nameuser1/DeepSeek-Coder-V2-Lite-Instruct-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Nameuser1/DeepSeek-Coder-V2-Lite-Instruct-GGUF to start chatting
- Docker Model Runner
How to use Nameuser1/DeepSeek-Coder-V2-Lite-Instruct-GGUF with Docker Model Runner:
docker model run hf.co/Nameuser1/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q5_K_M
- Lemonade
How to use Nameuser1/DeepSeek-Coder-V2-Lite-Instruct-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Nameuser1/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q5_K_M
Run and chat with the model
lemonade run user.DeepSeek-Coder-V2-Lite-Instruct-GGUF-Q5_K_M
List all available models
lemonade list
Upload 3 files
Browse files- config.json +59 -0
- tokenizer.json +0 -0
- tokenizer_config.json +35 -0
config.json
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{
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"architectures": [
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"DeepseekV2ForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"auto_map": {
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"AutoConfig": "configuration_deepseek.DeepseekV2Config",
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"AutoModel": "modeling_deepseek.DeepseekV2Model",
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"AutoModelForCausalLM": "modeling_deepseek.DeepseekV2ForCausalLM"
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},
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"aux_loss_alpha": 0.001,
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"bos_token_id": 100000,
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"eos_token_id": 100001,
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"first_k_dense_replace": 1,
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"hidden_act": "silu",
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"hidden_size": 2048,
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"initializer_range": 0.02,
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"intermediate_size": 10944,
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"kv_lora_rank": 512,
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"max_position_embeddings": 163840,
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"model_type": "deepseek_v2",
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"moe_intermediate_size": 1408,
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"moe_layer_freq": 1,
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"n_group": 1,
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"n_routed_experts": 64,
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"n_shared_experts": 2,
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"norm_topk_prob": false,
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"num_attention_heads": 16,
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"num_experts_per_tok": 6,
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"num_hidden_layers": 27,
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"num_key_value_heads": 16,
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"pretraining_tp": 1,
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"q_lora_rank": null,
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"qk_nope_head_dim": 128,
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"qk_rope_head_dim": 64,
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"rms_norm_eps": 1e-06,
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"rope_scaling": {
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"beta_fast": 32,
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"beta_slow": 1,
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"factor": 40,
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"mscale": 0.707,
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"mscale_all_dim": 0.707,
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"original_max_position_embeddings": 4096,
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"type": "yarn"
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},
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"rope_theta": 10000,
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"routed_scaling_factor": 1.0,
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"scoring_func": "softmax",
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"seq_aux": true,
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"tie_word_embeddings": false,
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"topk_group": 1,
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"topk_method": "greedy",
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"torch_dtype": "bfloat16",
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"transformers_version": "4.39.3",
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"use_cache": true,
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"v_head_dim": 128,
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"vocab_size": 102400
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}
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tokenizer.json
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tokenizer_config.json
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{
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"add_bos_token": true,
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"add_eos_token": false,
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"bos_token": {
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"__type": "AddedToken",
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"content": "<|begin▁of▁sentence|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"clean_up_tokenization_spaces": false,
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"eos_token": {
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"__type": "AddedToken",
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"content": "<|end▁of▁sentence|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"legacy": true,
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"model_max_length": 16384,
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"pad_token": {
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"__type": "AddedToken",
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"content": "<|end▁of▁sentence|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"sp_model_kwargs": {},
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"unk_token": null,
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"tokenizer_class": "LlamaTokenizerFast",
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"chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{{ bos_token }}{% for message in messages %}{% if message['role'] == 'user' %}{{ 'User: ' + message['content'] + '\n\n' }}{% elif message['role'] == 'assistant' %}{{ 'Assistant: ' + message['content'] + eos_token }}{% elif message['role'] == 'system' %}{{ message['content'] + '\n\n' }}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ 'Assistant:' }}{% endif %}"
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}
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