初始化项目，由ModelHub XC社区提供模型

Model: QuantFactory/SmolLM2-135M-GGUF
Source: Original Platform

.gitattributes

@@ -0,0 +1,49 @@
+*.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
+SmolLM2-135M.Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+SmolLM2-135M.Q4_1.gguf filter=lfs diff=lfs merge=lfs -text
+SmolLM2-135M.Q4_0.gguf filter=lfs diff=lfs merge=lfs -text
+SmolLM2-135M.Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
+SmolLM2-135M.Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
+SmolLM2-135M.Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+SmolLM2-135M.Q5_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+SmolLM2-135M.Q5_0.gguf filter=lfs diff=lfs merge=lfs -text
+SmolLM2-135M.Q5_1.gguf filter=lfs diff=lfs merge=lfs -text
+SmolLM2-135M.Q2_K.gguf filter=lfs diff=lfs merge=lfs -text
+SmolLM2-135M.Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text
+SmolLM2-135M.Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+SmolLM2-135M.Q3_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+SmolLM2-135M.Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,145 @@
+
+---
+
+library_name: transformers
+license: apache-2.0
+language:
+- en
+
+---
+
+[![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)](https://hf.co/QuantFactory)
+
+
+# QuantFactory/SmolLM2-135M-GGUF
+This is quantized version of [HuggingFaceTB/SmolLM2-135M](https://huggingface.co/HuggingFaceTB/SmolLM2-135M) created using llama.cpp
+
+# Original Model Card
+
+
+
+# SmolLM2
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/61c141342aac764ce1654e43/XtSR4NkriicR6fGiWGowZ.png)
+
+##  Table of Contents
+
+1. [Model Summary](##model-summary)
+2. [Limitations](##limitations)
+3. [Training](##training)
+4. [License](##license)
+5. [Citation](##citation)
+
+## Model Summary
+
+SmolLM2 is a family of compact language models available in three size: 135M, 360M, and 1.7B parameters. They are capable of solving a wide range of tasks while being lightweight enough to run on-device.
+
+SmolLM2 demonstrates significant advances over its predecessor SmolLM1, particularly in instruction following, knowledge, reasoning. The 135M model was trained on 2 trillion tokens using a diverse dataset combination: FineWeb-Edu, DCLM, The Stack, along with new filtered datasets we curated and will release soon.  We developed the instruct version through supervised fine-tuning (SFT) using a combination of public datasets and our own curated datasets. We then applied Direct Preference Optimization (DPO) using [UltraFeedback](https://huggingface.co/datasets/HuggingFaceH4/ultrafeedback_binarized).
+
+The instruct model additionally supports tasks such as text rewriting, summarization and function calling thanks to datasets developed by [Argilla](https://huggingface.co/argilla) such as [Synth-APIGen-v0.1](https://huggingface.co/datasets/argilla/Synth-APIGen-v0.1).
+
+### How to use
+
+```bash
+pip install transformers
+```
+
+#### Running the model on CPU/GPU/multi GPU
+* _Using full precision_
+```python
+# pip install transformers
+from transformers import AutoModelForCausalLM, AutoTokenizer
+checkpoint = "HuggingFaceTB/SmolLM2-135M"
+device = "cuda" # for GPU usage or "cpu" for CPU usage
+tokenizer = AutoTokenizer.from_pretrained(checkpoint)
+# for multiple GPUs install accelerate and do `model = AutoModelForCausalLM.from_pretrained(checkpoint, device_map="auto")`
+model = AutoModelForCausalLM.from_pretrained(checkpoint).to(device)
+inputs = tokenizer.encode("Gravity is", return_tensors="pt").to(device)
+outputs = model.generate(inputs)
+print(tokenizer.decode(outputs[0]))
+```
+
+* _Using `torch.bfloat16`_
+```python
+# pip install accelerate
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM
+checkpoint = "HuggingFaceTB/SmolLM2-135M"
+tokenizer = AutoTokenizer.from_pretrained(checkpoint)
+# for fp16 use `torch_dtype=torch.float16` instead
+model = AutoModelForCausalLM.from_pretrained(checkpoint, device_map="auto", torch_dtype=torch.bfloat16)
+inputs = tokenizer.encode("Gravity is", return_tensors="pt").to("cuda")
+outputs = model.generate(inputs)
+print(tokenizer.decode(outputs[0]))
+```
+```bash
+>>> print(f"Memory footprint: {model.get_memory_footprint() / 1e6:.2f} MB")
+Memory footprint: 723.56 MB
+```
+
+## Evaluation
+
+In this section, we report the evaluation results of SmolLM2. All evaluations are zero-shot unless stated otherwise, and we use [lighteval](https://github.com/huggingface/lighteval) to run them.
+
+## Base pre-trained model
+
+| Metrics            | SmolLM2-135M-8k | SmolLM-135M  |
+|:-------------------|:----------------:|:------------:|
+| HellaSwag         | **42.1**         | 41.2         |
+| ARC (Average)     | **43.9**         | 42.4         |
+| PIQA              | 68.4             | 68.4         |
+| MMLU (cloze)      | **31.5**         | 30.2         |
+| CommonsenseQA     | **33.9**         | 32.7         |
+| TriviaQA          | 4.1              | **4.3**      |
+| Winogrande        | 51.3             | 51.3         |
+| OpenBookQA        | **34.6**         | 34.0         |
+| GSM8K (5-shot)    | **1.4**          | 1.0          |
+
+
+## Instruction model
+
+| Metric                       | SmolLM2-135M-Instruct | SmolLM-135M-Instruct |
+|:-----------------------------|:---------------------:|:--------------------:|
+| IFEval (Average prompt/inst) | **29.9**                 | 17.2                |
+| MT-Bench                     | **1.98**                 | 1.68                |
+| HellaSwag                    | **40.9**                 | 38.9                |
+| ARC (Average)                | **37.3**                 | 33.9                |
+| PIQA                         | **66.3**                 | 64.0                |
+| MMLU (cloze)                 | **29.3**                 | 28.3                |
+| BBH (3-shot)                 | **28.2**                 | 25.2                |
+| GSM8K (5-shot)               | 1.4                  | 1.4                 |
+
+
+
+## Limitations
+
+SmolLM2 models primarily understand and generate content in English. They can produce text on a variety of topics, but the generated content may not always be factually accurate, logically consistent, or free from biases present in the training data. These models should be used as assistive tools rather than definitive sources of information. Users should always verify important information and critically evaluate any generated content.
+
+## Training
+
+### Model
+
+- **Architecture:** Transformer decoder
+- **Pretraining tokens:** 2T
+- **Precision:** bfloat16
+
+### Hardware
+
+- **GPUs:** 64 H100
+
+### Software
+
+- **Training Framework:** [nanotron](https://github.com/huggingface/nanotron/tree/main)
+
+## License
+
+[Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0)
+
+## Citation
+```bash
+@misc{allal2024SmolLM2,
+      title={SmolLM2 - with great data, comes great performance}, 
+      author={Loubna Ben Allal and Anton Lozhkov and Elie Bakouch and Gabriel Martín Blázquez and Lewis Tunstall and Agustín Piqueres and Andres Marafioti and Cyril Zakka and Leandro von Werra and Thomas Wolf},
+      year={2024},
+}
+```

SmolLM2-135M.Q2_K.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ccfefb4a20519e08f308247c91479c98ed04af311bb58701bdd652f729abfc36
+size 88201184

SmolLM2-135M.Q3_K_L.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:256d516bdf66723a84830cebca34bfe98dc61d2d2f375ef097169ffffaeeb6d1
+size 97532384

SmolLM2-135M.Q3_K_M.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b351018cbcdce99c802e30275ae89c9eed6127a3b2c7abfb3f6294007c8a42d6
+size 93509600

SmolLM2-135M.Q3_K_S.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1e3a65c54cd5b3be3cb2524848700862487be3ef97234784cc7387bf4bd7f9c6
+size 88201184

SmolLM2-135M.Q4_0.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6f96e054a48f8fcdb5814abc1203ca12c0f9cce2791ca9a5153caad8c3b5479b
+size 91726304

SmolLM2-135M.Q4_1.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0abf592e3d9880e26b455f8ee457909082bdb88ff2187d492addcebfdbad9388
+size 98361824

SmolLM2-135M.Q4_K_M.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b38d0237afc63fa77f35b9f82f394ac2116e77609514461d6bc51deec02a9c91
+size 105453536

SmolLM2-135M.Q4_K_S.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bd3436f16f8a9714823c436193917754c5c6ea6fcfb8e48c4ebc781a89e03094
+size 102039008

SmolLM2-135M.Q5_0.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9fecb117045a4ec6922e407a09dd1299c0de4fc49368ba061981b77ff98af24b
+size 104997344

SmolLM2-135M.Q5_1.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f4b25d36c10891278d367dc2f3463f495ba551dd73c2a3d20c662d46e4b8edf9
+size 111632864

SmolLM2-135M.Q5_K_M.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d7ca55946137aa448010df7c2ddd9f22cb7cb8fd04807f5e2dc17293572c84db
+size 112102880

SmolLM2-135M.Q5_K_S.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:150df2a8fe3445d293eeb5891f7cc512185f42888e846a1c9dc5df86251f9b8c
+size 109973984

SmolLM2-135M.Q6_K.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:72bf9cf9d0ea616f800e02461ca42b257def6afff22807fe6ec405ea3dae1db8
+size 138382304

SmolLM2-135M.Q8_0.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b761d9ccdfce67726e41ca2ef30e9dfbcf6a32ca2aaef47df5c049ec362d04cd
+size 144810464

configuration.json

@@ -0,0 +1 @@
+{"framework": "pytorch", "task": "others", "allow_remote": true}