初始化项目，由ModelHub XC社区提供模型

Model: hdnh2006/DeepSeek-R1-Distill-Qwen-1.5B-GGUF Source: Original Platform
2026-08-07 10:48:16 +08:00
commit dc9a26cdbb
17 changed files with 209 additions and 0 deletions
--- a/.gitattributes
+++ b/.gitattributes
@@ -0,0 +1,50 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+DeepSeek-R1-Distill-Qwen-1.5B-F16.gguf filter=lfs diff=lfs merge=lfs -text
+DeepSeek-R1-Distill-Qwen-1.5B-Q2_K.gguf filter=lfs diff=lfs merge=lfs -text
+DeepSeek-R1-Distill-Qwen-1.5B-Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text
+DeepSeek-R1-Distill-Qwen-1.5B-Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+DeepSeek-R1-Distill-Qwen-1.5B-Q3_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+DeepSeek-R1-Distill-Qwen-1.5B-Q4_0.gguf filter=lfs diff=lfs merge=lfs -text
+DeepSeek-R1-Distill-Qwen-1.5B-Q4_1.gguf filter=lfs diff=lfs merge=lfs -text
+DeepSeek-R1-Distill-Qwen-1.5B-Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+DeepSeek-R1-Distill-Qwen-1.5B-Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+DeepSeek-R1-Distill-Qwen-1.5B-Q5_0.gguf filter=lfs diff=lfs merge=lfs -text
+DeepSeek-R1-Distill-Qwen-1.5B-Q5_1.gguf filter=lfs diff=lfs merge=lfs -text
+DeepSeek-R1-Distill-Qwen-1.5B-Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+DeepSeek-R1-Distill-Qwen-1.5B-Q5_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+DeepSeek-R1-Distill-Qwen-1.5B-Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
+DeepSeek-R1-Distill-Qwen-1.5B-Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
--- a/DeepSeek-R1-Distill-Qwen-1.5B-F16.gguf
+++ b/DeepSeek-R1-Distill-Qwen-1.5B-F16.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:855f80dc0dbf54700d4b6928fe6e866d1bf1c0a4e92569087b66e5d6516e16a8
+size 3560416096
--- a/DeepSeek-R1-Distill-Qwen-1.5B-Q2_K.gguf
+++ b/DeepSeek-R1-Distill-Qwen-1.5B-Q2_K.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ef2fad904c270c919ef5b599d7a40e7301ec067c90f519739299a2a8bb3b3bf6
+size 752879968
--- a/DeepSeek-R1-Distill-Qwen-1.5B-Q3_K_L.gguf
+++ b/DeepSeek-R1-Distill-Qwen-1.5B-Q3_K_L.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0fca5f19e0b9e757895e98f23e82d896f55372cd51dea1daf6d6806b685825fa
+size 980439904
--- a/DeepSeek-R1-Distill-Qwen-1.5B-Q3_K_M.gguf
+++ b/DeepSeek-R1-Distill-Qwen-1.5B-Q3_K_M.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0b34867f5d0df299f828f9557425b24ccae8162e60e283eac099d7f216fac56d
+size 924455776
--- a/DeepSeek-R1-Distill-Qwen-1.5B-Q3_K_S.gguf
+++ b/DeepSeek-R1-Distill-Qwen-1.5B-Q3_K_S.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9ab0765bef785747347147f36de56c1321162a65cd0d864932b950a095ae3871
+size 861221728
--- a/DeepSeek-R1-Distill-Qwen-1.5B-Q4_0.gguf
+++ b/DeepSeek-R1-Distill-Qwen-1.5B-Q4_0.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2ff835372cf76ec644be7733b11a0fd9b875b7ff5249d38b24760012415bf3be
+size 1066227040
--- a/DeepSeek-R1-Distill-Qwen-1.5B-Q4_1.gguf
+++ b/DeepSeek-R1-Distill-Qwen-1.5B-Q4_1.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:43d00b64c800c11733936709032d63bac4eba1be67c9a9de0e65d95574cf635a
+size 1162700128
--- a/DeepSeek-R1-Distill-Qwen-1.5B-Q4_K_M.gguf
+++ b/DeepSeek-R1-Distill-Qwen-1.5B-Q4_K_M.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1d6995d3b87610c40874a81f20d3c188235ea281324e9f5a9ba52274c530da61
+size 1117320544
--- a/DeepSeek-R1-Distill-Qwen-1.5B-Q4_K_S.gguf
+++ b/DeepSeek-R1-Distill-Qwen-1.5B-Q4_K_S.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cb3cc4af5e4821d9ea8b9b9358a0fdc70b5825d4ecd8140ca046294b809906ed
+size 1071584608
--- a/DeepSeek-R1-Distill-Qwen-1.5B-Q5_0.gguf
+++ b/DeepSeek-R1-Distill-Qwen-1.5B-Q5_0.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e60648346bc87df5a2ee5b06b1caf9b3bfa50d0d20abecf8ef180d78a0db77c3
+size 1259173216
--- a/DeepSeek-R1-Distill-Qwen-1.5B-Q5_1.gguf
+++ b/DeepSeek-R1-Distill-Qwen-1.5B-Q5_1.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bd14abc394f58a01b20e15c778d255d0105d74021de09d083ee63cc1b4927d7f
+size 1355646304
--- a/DeepSeek-R1-Distill-Qwen-1.5B-Q5_K_M.gguf
+++ b/DeepSeek-R1-Distill-Qwen-1.5B-Q5_K_M.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b98429b4e04a008df33077f818d3d4469fb2902066520d3d4c10a6aa92e0c24c
+size 1285494112
--- a/DeepSeek-R1-Distill-Qwen-1.5B-Q5_K_S.gguf
+++ b/DeepSeek-R1-Distill-Qwen-1.5B-Q5_K_S.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d9f70217a789d28bb6b31c8771d64ec56d00335fd381a762eb3bc5483218bdd6
+size 1259173216
--- a/DeepSeek-R1-Distill-Qwen-1.5B-Q6_K.gguf
+++ b/DeepSeek-R1-Distill-Qwen-1.5B-Q6_K.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c64e11ba60210d14311ce91b9fa62938b5f73fe4fb863b554077f820d54d1e4f
+size 1464178528
--- a/DeepSeek-R1-Distill-Qwen-1.5B-Q8_0.gguf
+++ b/DeepSeek-R1-Distill-Qwen-1.5B-Q8_0.gguf
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0b2d8b13e948a20d836e9de919cb642bd76921ac70bb5c9f66d58e9df4f0d044
+size 1894531936
--- a/README.md
+++ b/README.md
@@ -0,0 +1,114 @@
+---
+license: apache-2.0
+base_model: deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
+tags:
+  - deepseek
+  - llama.cpp
+library_name: transformers
+pipeline_tag: text-generation
+quantized_by: hdnh2006
+---
+
+# DeepSeek-R1-Distill-Qwen-1.5B GGUF llama.cpp quantization by [Henry Navarro](https://henrynavarro.org) 🧠🤖
+
+
+This repository contains GGUF format model files for DeepSeek-R1-Distill-Qwen-1.5B, quantized using [llama.cpp](https://github.com/ggerganov/llama.cpp).
+
+All the models have been quantized following the [instructions](https://github.com/ggerganov/llama.cpp/blob/master/examples/quantize/README.md#quantize) provided by llama.cpp. This is:
+```bash
+# obtain the official LLaMA model weights and place them in ./models
+ls ./models
+llama-2-7b tokenizer_checklist.chk tokenizer.model
+# [Optional] for models using BPE tokenizers
+ls ./models
+<folder containing weights and tokenizer json> vocab.json
+# [Optional] for PyTorch .bin models like Mistral-7B
+ls ./models
+<folder containing weights and tokenizer json>
+
+# install Python dependencies
+python3 -m pip install -r requirements.txt
+
+# convert the model to ggml FP16 format
+python3 convert_hf_to_gguf.py models/mymodel/
+
+# quantize the model to 4-bits (using Q4_K_M method)
+./llama-quantize ./models/mymodel/ggml-model-f16.gguf ./models/mymodel/ggml-model-Q4_K_M.gguf Q4_K_M
+
+# update the gguf filetype to current version if older version is now unsupported
+./llama-quantize ./models/mymodel/ggml-model-Q4_K_M.gguf ./models/mymodel/ggml-model-Q4_K_M-v2.gguf COPY
+```
+
+
+## Model Details
+
+Original model: https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
+
+## Summary models 📋
+| Filename | Quant type | Description |
+| -------- | ---------- | ----------- |
+| [DeepSeek-R1-Distill-Qwen-1.5B-F16.gguf](https://huggingface.co/hdnh2006/DeepSeek-R1-Distill-Qwen-1.5B/blob/main/DeepSeek-R1-Distill-Qwen-1.5B-F16.gguf) | F16 | Half precision, no quantization applied |
+| [DeepSeek-R1-Distill-Qwen-1.5B-Q8_0.gguf](https://huggingface.co/hdnh2006/DeepSeek-R1-Distill-Qwen-1.5B/blob/main/DeepSeek-R1-Distill-Qwen-1.5B-Q8_0.gguf) | Q8_0 | 8-bit quantization, highest quality, largest size |
+| [DeepSeek-R1-Distill-Qwen-1.5B-Q6_K.gguf](https://huggingface.co/hdnh2006/DeepSeek-R1-Distill-Qwen-1.5B/blob/main/DeepSeek-R1-Distill-Qwen-1.5B-Q6_K.gguf) | Q6_K | 6-bit quantization, very high quality |
+| [DeepSeek-R1-Distill-Qwen-1.5B-Q5_1.gguf](https://huggingface.co/hdnh2006/DeepSeek-R1-Distill-Qwen-1.5B/blob/main/DeepSeek-R1-Distill-Qwen-1.5B-Q5_1.gguf) | Q5_1 | 5-bit quantization, good balance of quality and size |
+| [DeepSeek-R1-Distill-Qwen-1.5B-Q5_K_M.gguf](https://huggingface.co/hdnh2006/DeepSeek-R1-Distill-Qwen-1.5B/blob/main/DeepSeek-R1-Distill-Qwen-1.5B-Q5_K_M.gguf) | Q5_K_M | 5-bit quantization, good balance of quality and size |
+| [DeepSeek-R1-Distill-Qwen-1.5B-Q5_K_S.gguf](https://huggingface.co/hdnh2006/DeepSeek-R1-Distill-Qwen-1.5B/blob/main/DeepSeek-R1-Distill-Qwen-1.5B-Q5_K_S.gguf) | Q5_K_S | 5-bit quantization, good balance of quality and size |
+| [DeepSeek-R1-Distill-Qwen-1.5B-Q5_0.gguf](https://huggingface.co/hdnh2006/DeepSeek-R1-Distill-Qwen-1.5B/blob/main/DeepSeek-R1-Distill-Qwen-1.5B-Q5_0.gguf) | Q5_0 | 5-bit quantization, good balance of quality and size |
+| [DeepSeek-R1-Distill-Qwen-1.5B-Q4_1.gguf](https://huggingface.co/hdnh2006/DeepSeek-R1-Distill-Qwen-1.5B/blob/main/DeepSeek-R1-Distill-Qwen-1.5B-Q4_1.gguf) | Q4_1 | 4-bit quantization, balanced quality and size |
+| [DeepSeek-R1-Distill-Qwen-1.5B-Q4_K_M.gguf](https://huggingface.co/hdnh2006/DeepSeek-R1-Distill-Qwen-1.5B/blob/main/DeepSeek-R1-Distill-Qwen-1.5B-Q4_K_M.gguf) | Q4_K_M | 4-bit quantization, balanced quality and size |
+| [DeepSeek-R1-Distill-Qwen-1.5B-Q4_K_S.gguf](https://huggingface.co/hdnh2006/DeepSeek-R1-Distill-Qwen-1.5B/blob/main/DeepSeek-R1-Distill-Qwen-1.5B-Q4_K_S.gguf) | Q4_K_S | 4-bit quantization, balanced quality and size |
+| [DeepSeek-R1-Distill-Qwen-1.5B-Q4_0.gguf](https://huggingface.co/hdnh2006/DeepSeek-R1-Distill-Qwen-1.5B/blob/main/DeepSeek-R1-Distill-Qwen-1.5B-Q4_0.gguf) | Q4_0 | 4-bit quantization, balanced quality and size |
+| [DeepSeek-R1-Distill-Qwen-1.5B-Q3_K_L.gguf](https://huggingface.co/hdnh2006/DeepSeek-R1-Distill-Qwen-1.5B/blob/main/DeepSeek-R1-Distill-Qwen-1.5B-Q3_K_L.gguf) | Q3_K_L | 3-bit quantization, smaller size, lower quality |
+| [DeepSeek-R1-Distill-Qwen-1.5B-Q3_K_M.gguf](https://huggingface.co/hdnh2006/DeepSeek-R1-Distill-Qwen-1.5B/blob/main/DeepSeek-R1-Distill-Qwen-1.5B-Q3_K_M.gguf) | Q3_K_M | 3-bit quantization, smaller size, lower quality |
+| [DeepSeek-R1-Distill-Qwen-1.5B-Q3_K_S.gguf](https://huggingface.co/hdnh2006/DeepSeek-R1-Distill-Qwen-1.5B/blob/main/DeepSeek-R1-Distill-Qwen-1.5B-Q3_K_S.gguf) | Q3_K_S | 3-bit quantization, smaller size, lower quality |
+| [DeepSeek-R1-Distill-Qwen-1.5B-Q2_K.gguf](https://huggingface.co/hdnh2006/DeepSeek-R1-Distill-Qwen-1.5B/blob/main/DeepSeek-R1-Distill-Qwen-1.5B-Q2_K.gguf) | Q2_K | 2-bit quantization, smallest size, lowest quality |
+
+
+## Usage with Ollama 🦙
+
+### Direct from Ollama
+```
+ollama run hdnh2006/DeepSeek-R1-Distill-Qwen-1.5B
+```
+
+## Download Models Using huggingface-cli 🤗
+
+### Installation of `huggingface_hub[cli]`
+```bash
+pip install -U "huggingface_hub[cli]"
+```
+
+### Downloading Specific Model Files
+```bash
+huggingface-cli download hdnh2006/DeepSeek-R1-Distill-Qwen-1.5B --include "DeepSeek-R1-Distill-Qwen-1.5B-Q4_K_M.gguf" --local-dir ./
+```
+
+## Which File Should I Choose? 📈
+
+A comprehensive analysis with performance charts is provided by Artefact2 [here](https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9).
+
+### Assessing System Capabilities
+1. **Determine Your Model Size**: Start by checking the amount of RAM and VRAM available in your system. This will help you decide the largest possible model you can run.
+2. **Optimizing for Speed**:
+    - **GPU Utilization**: To run your model as quickly as possible, aim to fit the entire model into your GPU's VRAM. Pick a version that’s 1-2GB smaller than the total VRAM.
+3. **Maximizing Quality**:
+    - **Combined Memory**: For the highest possible quality, sum your system RAM and GPU's VRAM. Then choose a model that's 1-2GB smaller than this combined total.
+
+### Deciding Between 'I-Quant' and 'K-Quant'
+1. **Simplicity**:
+    - **K-Quant**: If you prefer a straightforward approach, select a K-quant model. These are labeled as 'QX_K_X', such as Q5_K_M.
+2. **Advanced Configuration**:
+    - **Feature Chart**: For a more nuanced choice, refer to the [llama.cpp feature matrix](https://github.com/ggerganov/llama.cpp/wiki/Feature-matrix).
+    - **I-Quant Models**: Best suited for configurations below Q4 and for systems running cuBLAS (Nvidia) or rocBLAS (AMD). These are labeled 'IQX_X', such as IQ3_M, and offer better performance for their size.
+    - **Compatibility Considerations**:
+        - **I-Quant Models**: While usable on CPU and Apple Metal, they perform slower compared to their K-quant counterparts. The choice between speed and performance becomes a significant tradeoff.
+        - **AMD Cards**: Verify if you are using the rocBLAS build or the Vulkan build. I-quants are not compatible with Vulkan.
+        - **Current Support**: At the time of writing, LM Studio offers a preview with ROCm support, and other inference engines provide specific ROCm builds.
+
+By following these guidelines, you can make an informed decision on which file best suits your system and performance needs.
+
+
+## Contact 🌐
+Website: henrynavarro.org
+
+Email: public.contact.rerun407@simplelogin.com