Instructions to use second-state/DeepSeek-Coder-V2-Instruct-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use second-state/DeepSeek-Coder-V2-Instruct-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="second-state/DeepSeek-Coder-V2-Instruct-GGUF",
	filename="DeepSeek-Coder-V2-Instruct-Q2_K-00001-of-00003.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 second-state/DeepSeek-Coder-V2-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 second-state/DeepSeek-Coder-V2-Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf second-state/DeepSeek-Coder-V2-Instruct-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf second-state/DeepSeek-Coder-V2-Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf second-state/DeepSeek-Coder-V2-Instruct-GGUF: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 second-state/DeepSeek-Coder-V2-Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf second-state/DeepSeek-Coder-V2-Instruct-GGUF: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 second-state/DeepSeek-Coder-V2-Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf second-state/DeepSeek-Coder-V2-Instruct-GGUF:Q4_K_M

Use Docker

docker model run hf.co/second-state/DeepSeek-Coder-V2-Instruct-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use second-state/DeepSeek-Coder-V2-Instruct-GGUF with Ollama:
```
ollama run hf.co/second-state/DeepSeek-Coder-V2-Instruct-GGUF:Q4_K_M
```

Unsloth Studio new

How to use second-state/DeepSeek-Coder-V2-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 second-state/DeepSeek-Coder-V2-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 second-state/DeepSeek-Coder-V2-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 second-state/DeepSeek-Coder-V2-Instruct-GGUF to start chatting

Docker Model Runner
How to use second-state/DeepSeek-Coder-V2-Instruct-GGUF with Docker Model Runner:
```
docker model run hf.co/second-state/DeepSeek-Coder-V2-Instruct-GGUF:Q4_K_M
```

Lemonade

How to use second-state/DeepSeek-Coder-V2-Instruct-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull second-state/DeepSeek-Coder-V2-Instruct-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.DeepSeek-Coder-V2-Instruct-GGUF-Q4_K_M

List all available models

lemonade list

apepkuss79 commited on Aug 4, 2024

Commit

85b248c

verified ·

1 Parent(s): 22b3d01

Upload config.json with huggingface_hub

Browse files

Files changed (1) hide show

config.json +60 -0

config.json ADDED Viewed

	@@ -0,0 +1,60 @@

+{
+  "architectures": [
+    "DeepseekV2ForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "auto_map": {
+    "AutoConfig": "configuration_deepseek.DeepseekV2Config",
+    "AutoModel": "modeling_deepseek.DeepseekV2Model",
+    "AutoModelForCausalLM": "modeling_deepseek.DeepseekV2ForCausalLM"
+  },
+  "aux_loss_alpha": 0.001,
+  "bos_token_id": 100000,
+  "eos_token_id": 100001,
+  "ep_size": 1,
+  "first_k_dense_replace": 1,
+  "hidden_act": "silu",
+  "hidden_size": 5120,
+  "initializer_range": 0.02,
+  "intermediate_size": 12288,
+  "kv_lora_rank": 512,
+  "max_position_embeddings": 163840,
+  "model_type": "deepseek_v2",
+  "moe_intermediate_size": 1536,
+  "moe_layer_freq": 1,
+  "n_group": 8,
+  "n_routed_experts": 160,
+  "n_shared_experts": 2,
+  "norm_topk_prob": false,
+  "num_attention_heads": 128,
+  "num_experts_per_tok": 6,
+  "num_hidden_layers": 60,
+  "num_key_value_heads": 128,
+  "pretraining_tp": 1,
+  "q_lora_rank": 1536,
+  "qk_nope_head_dim": 128,
+  "qk_rope_head_dim": 64,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": {
+    "beta_fast": 32,
+    "beta_slow": 1,
+    "factor": 40,
+    "mscale": 1.0,
+    "mscale_all_dim": 1.0,
+    "original_max_position_embeddings": 4096,
+    "type": "yarn"
+  },
+  "rope_theta": 10000,
+  "routed_scaling_factor": 16.0,
+  "scoring_func": "softmax",
+  "seq_aux": true,
+  "tie_word_embeddings": false,
+  "topk_group": 3,
+  "topk_method": "group_limited_greedy",
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.39.3",
+  "use_cache": true,
+  "v_head_dim": 128,
+  "vocab_size": 102400
+}