初始化项目，由ModelHub XC社区提供模型

Model: QuantFactory/T-lite-instruct-0.1-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
+T-lite-instruct-0.1.Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+T-lite-instruct-0.1.Q4_1.gguf filter=lfs diff=lfs merge=lfs -text
+T-lite-instruct-0.1.Q4_0.gguf filter=lfs diff=lfs merge=lfs -text
+T-lite-instruct-0.1.Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
+T-lite-instruct-0.1.Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
+T-lite-instruct-0.1.Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+T-lite-instruct-0.1.Q5_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+T-lite-instruct-0.1.Q5_0.gguf filter=lfs diff=lfs merge=lfs -text
+T-lite-instruct-0.1.Q5_1.gguf filter=lfs diff=lfs merge=lfs -text
+T-lite-instruct-0.1.Q2_K.gguf filter=lfs diff=lfs merge=lfs -text
+T-lite-instruct-0.1.Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text
+T-lite-instruct-0.1.Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+T-lite-instruct-0.1.Q3_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+T-lite-instruct-0.1.Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,165 @@
+
+---
+
+language:
+- ru
+pipeline_tag: text-generation
+---
+
+![](https://cdn.discordapp.com/attachments/791342238541152306/1264099835221381251/image.png?ex=669ca436&is=669b52b6&hm=129f56187c31e1ed22cbd1bcdbc677a2baeea5090761d2f1a458c8b1ec7cca4b&)
+
+# QuantFactory/T-lite-instruct-0.1-GGUF
+This is quantized version of [AnatoliiPotapov/T-lite-instruct-0.1](https://huggingface.co/AnatoliiPotapov/T-lite-instruct-0.1) created using llama.cpp
+
+# Original Model Card
+
+
+# T-lite-instruct-0.1
+
+**🚨 T-lite is designed for further fine-tuning and is not intended as a ready-to-use conversational assistant. Users are advised to exercise caution and are responsible for any additional training and oversight required to ensure the model's responses meet acceptable ethical and safety standards. The responsibility for incorporating this model into industrial or commercial solutions lies entirely with those who choose to deploy it.**
+
+
+## Description
+
+T-lite-instruct-0.1 is an instruct version of the T-lite-0.1 model.
+
+T-lite-instruct-0.1 was trained in bf16. 
+
+
+### 📚 Dataset
+
+#### Contexts
+For the instruction dataset, the contexts are obtained from:
+- Open Source English-language datasets (such as UltraFeedback, HelpSteer, SHP, and so on)
+- Translations of English-language datasets through machine translation
+- Synthetic grounded QA contexts, generated from pre-training datasets
+
+The translated contexts are filtered using classifiers.
+
+#### SFT
+The responses to the contexts are generated by a strong model and the training is exclusively carried out on these responses. This avoids training the model on poor-quality translations.
+
+#### Reward Modeling
+RM is trained on such pairs:
+- Strong Model > Our Model
+- Stronger Model > Weaker Model
+- Chosen Translated Response > Rejected Translated Response
+- Pairs from original English datasets
+
+The translated preference data are preliminarily filtered by the RM ensemble.
+
+#### Preference tuning
+Two stages were used in preference tuning:
+- Stage 1: SPiN on the responses of the teacher model (Strong Model > Our Model)
+- Stage 2: SLiC-HF using our RM 
+
+
+## 📊 Benchmarks
+
+Here we present the results of T-lite-instruct-0.1 on automatic benchmarks.
+
+### 🏆 [MT-Bench](https://huggingface.co/spaces/lmsys/mt-bench)
+
+This benchmark was carefully translated into Russian and measured with [LLM Judge](https://github.com/lm-sys/FastChat/tree/main/fastchat/llm_judge) codebase, using gpt-4-1106-preview as a judge.
+
+<style>
+    table {
+        width: auto;
+    }
+    th, td {
+        padding: 5px;
+    }
+</style>
+| MT-Bench                                                        | Total       | Turn_1       | Turn_2       | coding | humanities | math | reasoning | roleplay | stem | writing |
+|-----------------------------------------------------------------|:-----------:|:------------:|:------------:|:------:|:----------:|:----:|:---------:|:--------:|:----:|:-------:|
+| **T-lite-instruct-0.1**                                         |  **6.458**   | **6.833**   | 6.078        | 4.136  |  **8.45**  | 4.25 | **4.5**   |**7.667** |**7.7**| 7.706  |
+| gpt3.5-turbo-0125                                               |  6.373      | 6.423        | **6.320**    |**6.519**| 7.474     | 4.75 | 4.15      |  6.333   | 6.7  |  7.588  |
+| suzume-llama-3-8B-multilingual-orpo-borda-half                  |  6.051      | 6.577        | 5.526        | 4.318  |  8.0       | 4.0  |  3.6      |  7.056   | 6.7  |  **7.889**  |
+| Qwen2-7b-Instruct                                               |  6.026      | 6.449        | 5.603        | 5.0    |  6.95      |**5.8**|  4.15    |  7.167   | 5.85 |  7.278  |
+| Llama-3-8b-Instruct                                             |  5.948      | 6.662        | 5.224        | 4.727  |  7.8       | 3.9  |  2.8      |  7.333   | 6.053 | 7.0    |
+| suzume-llama-3-8B-multilingual                                  |  5.808      | 6.167        | 5.449        | 5.409  |  6.4       | 5.05 |  3.8      |  6.556   | 5.0  |  7.056  |
+| saiga_llama3_8b                                                 |  5.471      | 5.896        | 5.039        | 3.0    |  7.4       | 3.55 |  3.5      |  6.444   | 5.15 | 7.812   |
+| Mistral-7B-Instruct-v0.3                                        |  5.135      | 5.679        | 4.584        | 4.045  |  6.35      | 3.15 |  3.2      |  5.765   | 5.2  | 7.333   |
+
+
+### 🏟️ [Arena](https://github.com/lm-sys/arena-hard-auto)
+
+We used Russian version of Arena benchmark from [Vikhrmodels](https://huggingface.co/datasets/Vikhrmodels/ru-arena-general) and [Arena Hard Auto](https://github.com/lm-sys/arena-hard-auto) codebase
+for evaluation. As baseline model we chose gpt3.5-turbo-0125 and the judge was gpt-4-1106-preview.
+
+<style>
+    table {
+        width: auto;
+    }
+    th, td {
+        padding: 5px;
+    }
+</style>
+| Arena General                                                   |   Score     |    95% CI    | Average Tokens |
+|-----------------------------------------------------------------|:-----------:|:------------:|:--------------:|
+| **T-lite-instruct-0.1**                                         |  **57.26**  | -2.9/2       | 870            | 
+| gpt3.5-turbo-0125                                               |  50         | 0/0          | 254            |
+| suzume-llama-3-8B-multilingual-orpo-borda-half                  |  47.17      | -2.6/2.4     | 735            |
+| Llama-3-8b-Instruct                                             |  42.16      | -2.1/2.1     | 455            |
+| saiga_llama3_8b                                                 |  39.88      | -2.3/2.5     | 616            |
+| suzume-llama-3-8B-multilingual                                  |  38.25      | -1.7/1.7     | 625            |
+| Qwen2-7b-Instruct                                               |  33.42      | -1.9/2.2     | 365            |
+| Mistral-7B-Instruct-v0.3                                        |  28.11      | -2/2.2       | 570            |
+
+
+## 👨‍💻 Examples of usage
+
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+torch.manual_seed(42)
+
+model_name = "t-bank-ai/T-lite-instruct-0.1"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto")
+
+messages = [
+    {"role": "user", "content": "Напиши рецепт классной пиццы!"},
+]
+
+input_ids = tokenizer.apply_chat_template(
+    messages,
+    add_generation_prompt=True,
+    return_tensors="pt"
+).to(model.device)
+
+terminators = [
+    tokenizer.eos_token_id,
+    tokenizer.convert_tokens_to_ids("<|eot_id|>")
+]
+
+outputs = model.generate(
+    input_ids,
+    max_new_tokens=256,
+    eos_token_id=terminators,
+)
+
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+Output:
+```
+Конечно, вот рецепт для вкусной домашней пиццы, который можно адаптировать под разные вкусы и предпочтения. Важно, чтобы тесто было мягким и воздушным, а начинка — сочной и ароматной.
+
+### Ингредиенты для теста:
+- 500 г муки (лучше использовать смесь пшеничной и цельнозерновой)
+- 1 ч. л. сухих дрожжей (или 7 г свежих)
+- 1 ч. л. сахара
+- 1 ч. л. соли
+- 1 ст. л. оливкового масла
+- 300 мл тёплой воды
+- 1 яйцо (для смазки)
+
+### Ингредиенты для начинки (примерный набор):
+- 200 г томатного соуса (можно сделать самому из свежих помидоров или использовать готовый)
+- 200 г моцареллы, нарезанной ломтиками
+- 100 г сыра пармезан (тертый)
+- 100 г ветчины или колбасы
+- 100 г грибов (шампин
+```

T-lite-instruct-0.1.Q2_K.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f4bfe28ff5d5e73946af49e151fe04dd217cc9cbf1c2d2f09e06970a2a3e86fe
+size 3179145536

T-lite-instruct-0.1.Q3_K_L.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9a0afc51bd1593c2261c679dcc21c2c71adee74811d31c2763df5970db28260c
+size 4321971744

T-lite-instruct-0.1.Q3_K_M.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bc340a2e0cfe91f57b4e76741988c360362c714cb57e2ac2f0cae0b7cce46710
+size 4018933280

T-lite-instruct-0.1.Q3_K_S.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5880c4df1d89aaca4dbc700343232855235e2a981a3e987be2086d37554081bb
+size 3664514592

T-lite-instruct-0.1.Q4_0.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bd523336f7ee104d6d61777788f21c871a9176ef656d3329c425bc3805309f84
+size 4661228672

T-lite-instruct-0.1.Q4_1.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6bfb123126ca24f8f9684b312f72a9bffb6eb517b88890dec1eb52d7861fbd7f
+size 5130270592

T-lite-instruct-0.1.Q4_K_M.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:83aa1c0edc58978427c268cad176931a209541462c2453fff8c5a05b2d7735e0
+size 4920751232

T-lite-instruct-0.1.Q4_K_S.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7c9b77b8b279fa059af04158cee6d796e6da5fad05e9b6853310686a10138456
+size 4692685952

T-lite-instruct-0.1.Q5_0.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:28a859554af8d259f2af71987b42fa1163dbdd7e6145d79d1946ba49c04f8bae
+size 5599312512

T-lite-instruct-0.1.Q5_1.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:36aa344ceb4b4bc3738182f6fdd86ca49069f103963b87a7fd7c5f66ed1a40e2
+size 6068354432

T-lite-instruct-0.1.Q5_K_M.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:923552ff2fa9628b011f8f1c53ee38caf35a9ee07a983d86a1aaf406b2bd839b
+size 5733005952

T-lite-instruct-0.1.Q5_K_S.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2fc93f06aced0c18f69d54b87627299244b1b3efc7940601a05301b003c459d8
+size 5599312512

T-lite-instruct-0.1.Q6_K.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3827627efa94abf5ea8328449437850d7fefddee85abef08fcb09dcf642282b4
+size 6596026592

T-lite-instruct-0.1.Q8_0.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:49e528a09efaa9100fbc3b1ad5dd1f09c2bb9f74f715c0247d146c80639ffb4a
+size 8540796960

configuration.json

@@ -0,0 +1 @@
+{}