Instructions to use Mauro6519/DeepSeek-R1-Medical-COT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Mauro6519/DeepSeek-R1-Medical-COT with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Mauro6519/DeepSeek-R1-Medical-COT", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use Mauro6519/DeepSeek-R1-Medical-COT 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 Mauro6519/DeepSeek-R1-Medical-COT:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Mauro6519/DeepSeek-R1-Medical-COT:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Mauro6519/DeepSeek-R1-Medical-COT:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Mauro6519/DeepSeek-R1-Medical-COT: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 Mauro6519/DeepSeek-R1-Medical-COT:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf Mauro6519/DeepSeek-R1-Medical-COT: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 Mauro6519/DeepSeek-R1-Medical-COT:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Mauro6519/DeepSeek-R1-Medical-COT:Q4_K_M

Use Docker

docker model run hf.co/Mauro6519/DeepSeek-R1-Medical-COT:Q4_K_M

LM Studio
Jan
Ollama
How to use Mauro6519/DeepSeek-R1-Medical-COT with Ollama:
```
ollama run hf.co/Mauro6519/DeepSeek-R1-Medical-COT:Q4_K_M
```

Unsloth Studio

How to use Mauro6519/DeepSeek-R1-Medical-COT 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 Mauro6519/DeepSeek-R1-Medical-COT 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 Mauro6519/DeepSeek-R1-Medical-COT to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Mauro6519/DeepSeek-R1-Medical-COT to start chatting

Docker Model Runner
How to use Mauro6519/DeepSeek-R1-Medical-COT with Docker Model Runner:
```
docker model run hf.co/Mauro6519/DeepSeek-R1-Medical-COT:Q4_K_M
```

Lemonade

How to use Mauro6519/DeepSeek-R1-Medical-COT with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Mauro6519/DeepSeek-R1-Medical-COT:Q4_K_M

Run and chat with the model

lemonade run user.DeepSeek-R1-Medical-COT-Q4_K_M

List all available models

lemonade list

Atomic Chat

Mauro6519 commited on Feb 3, 2025

Commit

cb432d6

verified ·

1 Parent(s): 324535c

Trained with Unsloth

Browse files

Files changed (3) hide show

config.json +19 -25
generation_config.json +3 -3
pytorch_model.bin +3 -0

config.json CHANGED Viewed

@@ -1,39 +1,33 @@
 {
-  "_name_or_path": "unsloth/deepseek-r1-distill-llama-8b-unsloth-bnb-4bit",
   "architectures": [
-    "LlamaForCausalLM"
   ],
-  "attention_bias": false,
   "attention_dropout": 0.0,
-  "bos_token_id": 128000,
-  "eos_token_id": 128001,
-  "head_dim": 128,
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-  "hidden_size": 4096,
   "initializer_range": 0.02,
-  "intermediate_size": 14336,
   "max_position_embeddings": 131072,
-  "mlp_bias": false,
-  "model_type": "llama",
-  "num_attention_heads": 32,
-  "num_hidden_layers": 32,
-  "num_key_value_heads": 8,
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-  "pretraining_tp": 1,
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-    "high_freq_factor": 4.0,
-    "low_freq_factor": 1.0,
-    "original_max_position_embeddings": 8192,
-    "rope_type": "llama3"
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-  "rope_theta": 500000.0,
   "tie_word_embeddings": false,
   "torch_dtype": "float16",
   "transformers_version": "4.47.1",
   "unsloth_fixed": true,
   "unsloth_version": "2025.1.8",
   "use_cache": true,
-  "vocab_size": 128256
 }

 {
+  "_name_or_path": "unsloth/deepseek-r1-distill-qwen-1.5b-unsloth-bnb-4bit",
   "architectures": [
+    "Qwen2ForCausalLM"
   ],
   "attention_dropout": 0.0,
+  "bos_token_id": 151646,
+  "eos_token_id": 151643,
   "hidden_act": "silu",
+  "hidden_size": 1536,
   "initializer_range": 0.02,
+  "intermediate_size": 8960,
   "max_position_embeddings": 131072,
+  "max_window_layers": 21,
+  "model_type": "qwen2",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 28,
+  "num_key_value_heads": 2,
+  "pad_token_id": 151654,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 10000,
+  "sliding_window": null,
   "tie_word_embeddings": false,
   "torch_dtype": "float16",
   "transformers_version": "4.47.1",
   "unsloth_fixed": true,
   "unsloth_version": "2025.1.8",
   "use_cache": true,
+  "use_mrope": false,
+  "use_sliding_window": false,
+  "vocab_size": 151936
 }

generation_config.json CHANGED Viewed

@@ -1,10 +1,10 @@
 {
   "_from_model_config": true,
-  "bos_token_id": 128000,
   "do_sample": true,
-  "eos_token_id": 128001,
   "max_length": 131072,
-  "pad_token_id": 128004,
   "temperature": 0.6,
   "top_p": 0.95,
   "transformers_version": "4.47.1"

 {
   "_from_model_config": true,
+  "bos_token_id": 151646,
   "do_sample": true,
+  "eos_token_id": 151643,
   "max_length": 131072,
+  "pad_token_id": 151654,
   "temperature": 0.6,
   "top_p": 0.95,
   "transformers_version": "4.47.1"

pytorch_model.bin ADDED Viewed

	@@ -0,0 +1,3 @@

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