初始化项目,由ModelHub XC社区提供模型

Model: tolgadev/Trendyol-LLM-7b-chat-v0.1-GGUF
Source: Original Platform
This commit is contained in:
ModelHub XC
2026-05-29 13:24:17 +08:00
commit ce5cbbd1a7
16 changed files with 290 additions and 0 deletions

47
.gitattributes vendored Normal file
View File

@@ -0,0 +1,47 @@
*.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
trendyol-llm-7b-chat-v0.1.Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
trendyol-llm-7b-chat-v0.1.Q5_K_S.gguf filter=lfs diff=lfs merge=lfs -text
trendyol-llm-7b-chat-v0.1.Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
trendyol-llm-7b-chat-v0.1.Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
trendyol-llm-7b-chat-v0.1.Q2_K.gguf filter=lfs diff=lfs merge=lfs -text
trendyol-llm-7b-chat-v0.1.Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text
trendyol-llm-7b-chat-v0.1.Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text
trendyol-llm-7b-chat-v0.1.Q3_K_S.gguf filter=lfs diff=lfs merge=lfs -text
trendyol-llm-7b-chat-v0.1.Q4_0.gguf filter=lfs diff=lfs merge=lfs -text
trendyol-llm-7b-chat-v0.1.Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
trendyol-llm-7b-chat-v0.1.Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text
trendyol-llm-7b-chat-v0.1.Q5_0.gguf filter=lfs diff=lfs merge=lfs -text

178
README.md Normal file
View File

@@ -0,0 +1,178 @@
---
model_name: Trendyol-LLM-7b-chat-v0.1
model_creator: Trendyol
base_model: Trendyol/Trendyol-LLM-7b-chat-v0.1
language:
- tr
- en
pipeline_tag: text-generation
license: apache-2.0
model_type: llama
library_name: transformers
inference: false
tags:
- trendyol
- llama-2
- turkish
quantized_by: tolgadev
---
## Trendyol-LLM-7b-chat-v0.1-GGUF models
----
## Description
This repo contains all types of GGUF formatted model files for [Trendyol-LLM-7b-chat-v0.1](https://huggingface.co/Trendyol/Trendyol-LLM-7b-chat-v0.1).
<img src="https://huggingface.co/Trendyol/Trendyol-LLM-7b-chat-v0.1/resolve/main/llama-tr-image.jpeg"
alt="drawing" width="400"/>
## Quantized LLM models and methods
| Name | Quant method | Bits | Size | Max RAM required | Use case |
| ---- | ---- | ---- | ---- | ---- | ----- |
| [Trendyol-LLM-7b-chat-v0.1.Q2_K.gguf](https://huggingface.co/tolgadev/Trendyol-LLM-7b-chat-v0.1-GGUF/blob/main/trendyol-llm-7b-chat-v0.1.Q2_K.gguf) | Q2_K | 2 | 2.59 GB| 4.88 GB | smallest, significant quality loss - not recommended for most purposes |
| [Trendyol-LLM-7b-chat-v0.1.Q3_K_S.gguf](https://huggingface.co/tolgadev/Trendyol-LLM-7b-chat-v0.1-GGUF/blob/main/trendyol-llm-7b-chat-v0.1.Q3_K_S.gguf) | Q3_K_S | 3 | 3.01 GB| 5.56 GB | very small, high quality loss |
| [Trendyol-LLM-7b-chat-v0.1.Q3_K_M.gguf](https://huggingface.co/tolgadev/Trendyol-LLM-7b-chat-v0.1-GGUF/blob/main/trendyol-llm-7b-chat-v0.1.Q3_K_M.gguf) | Q3_K_M | 3 | 3.36 GB| 5.91 GB | very small, high quality loss |
| [Trendyol-LLM-7b-chat-v0.1.Q3_K_L.gguf](https://huggingface.co/tolgadev/Trendyol-LLM-7b-chat-v0.1-GGUF/blob/main/trendyol-llm-7b-chat-v0.1.Q3_K_L.gguf) | Q3_K_L | 3 | 3.66 GB| 6.20 GB | small, substantial quality loss |
| [Trendyol-LLM-7b-chat-v0.1.Q4_0.gguf](https://huggingface.co/tolgadev/Trendyol-LLM-7b-chat-v0.1-GGUF/blob/main/trendyol-llm-7b-chat-v0.1.Q4_0.gguf) | Q4_0 | 4 | 3.9 GB| 6.45 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [Trendyol-LLM-7b-chat-v0.1.Q4_K_S.gguf](https://huggingface.co/tolgadev/Trendyol-LLM-7b-chat-v0.1-GGUF/blob/main/trendyol-llm-7b-chat-v0.1.Q4_K_S.gguf) | Q4_K_S | 4 | 3.93 GB| 6.48 GB | small, greater quality loss |
| [Trendyol-LLM-7b-chat-v0.1.Q4_K_M.gguf](https://huggingface.co/tolgadev/Trendyol-LLM-7b-chat-v0.1-GGUF/blob/main/trendyol-llm-7b-chat-v0.1.Q4_K_M.gguf) | Q4_K_M | 4 | 4.15 GB| 6.69 GB | medium, balanced quality - recommended |
| [Trendyol-LLM-7b-chat-v0.1.Q5_0.gguf](https://huggingface.co/tolgadev/Trendyol-LLM-7b-chat-v0.1-GGUF/blob/main/trendyol-llm-7b-chat-v0.1.Q5_0.gguf) | Q5_0 | 5 | 4.73 GB| 7.15 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [Trendyol-LLM-7b-chat-v0.1.Q5_K_S.gguf](https://huggingface.co/tolgadev/Trendyol-LLM-7b-chat-v0.1-GGUF/blob/main/trendyol-llm-7b-chat-v0.1.Q5_K_S.gguf) | Q5_K_S | 5 | 4.75 GB| 7.27 GB | large, low quality loss - recommended |
| [Trendyol-LLM-7b-chat-v0.1.Q5_K_M.gguf](https://huggingface.co/tolgadev/Trendyol-LLM-7b-chat-v0.1-GGUF/blob/main/trendyol-llm-7b-chat-v0.1.Q5_K_M.gguf) | Q5_K_M | 5 | 4.86 GB| 7.40 GB | large, very low quality loss - recommended |
| [Trendyol-LLM-7b-chat-v0.1.Q6_K.gguf](https://huggingface.co/tolgadev/Trendyol-LLM-7b-chat-v0.1-GGUF/blob/main/trendyol-llm-7b-chat-v0.1.Q6_K.gguf) | Q6_K | 6 | 5.61 GB| 8.15 GB | very large, extremely low quality loss |
| [Trendyol-LLM-7b-chat-v0.1.Q8_0.gguf](https://huggingface.co/tolgadev/Trendyol-LLM-7b-chat-v0.1-GGUF/blob/main/trendyol-llm-7b-chat-v0.1.Q8_0.gguf) | Q8_0 | 8 | 7.27 GB| 9.81 GB | very large, extremely low quality loss - not recommended |
The names of the quantization methods follow the naming convention: "q" + the number of bits + the variant used (detailed below). Here is a list of all the models and their corresponding use cases, based on model cards made by [TheBloke](https://huggingface.co/TheBloke/):
* `q2_k`: Uses Q4_K for the attention.vw and feed_forward.w2 tensors, Q2_K for the other tensors.
* `q3_k_l`: Uses Q5_K for the attention.wv, attention.wo, and feed_forward.w2 tensors, else Q3_K
* `q3_k_m`: Uses Q4_K for the attention.wv, attention.wo, and feed_forward.w2 tensors, else Q3_K
* `q3_k_s`: Uses Q3_K for all tensors
* `q4_0`: Original quant method, 4-bit.
* `q4_1`: Higher accuracy than q4_0 but not as high as q5_0. However has quicker inference than q5 models.
* `q4_k_m`: Uses Q6_K for half of the attention.wv and feed_forward.w2 tensors, else Q4_K
* `q4_k_s`: Uses Q4_K for all tensors
* `q5_0`: Higher accuracy, higher resource usage and slower inference.
* `q5_1`: Even higher accuracy, resource usage and slower inference.
* `q5_k_m`: Uses Q6_K for half of the attention.wv and feed_forward.w2 tensors, else Q5_K
* `q5_k_s`: Uses Q5_K for all tensors
* `q6_k`: Uses Q8_K for all tensors
* `q8_0`: Almost indistinguishable from float16. High resource use and slow. Not recommended for most users.
**TheBloke recommends using Q5_K_M** as it preserves most of the model's performance.
Alternatively, you can use Q4_K_M if you want to save some memory.
In general, K_M versions are better than K_S versions.
## How to download GGUF files
**Note for manual downloaders:** You almost never want to clone the entire repo! Multiple different quantisation formats are provided, and most users only want to pick and download a single file.
The following clients/libraries will automatically download models for you, providing a list of available models to choose from:
- LM Studio
- LoLLMS Web UI
- Faraday.dev
## Special thanks to [TheBloke on Huggingface](https://huggingface.co/TheBloke) and [Maxime Labonne on Github](https://github.com/mlabonne/llm-course)
-----
## Model Details
<img src="https://huggingface.co/Trendyol/Trendyol-LLM-7b-chat-v0.1/resolve/main/llama-tr-image.jpeg"
alt="drawing" width="400"/>
# **Trendyol LLM**
Trendyol LLM is a generative model that is based on LLaMa2 7B model. This is the repository for the chat model.
## Model Details
**Model Developers** Trendyol
**Variations** base and chat variations.
**Input** Models input text only.
**Output** Models generate text only.
**Model Architecture** Trendyol LLM is an auto-regressive language model (based on LLaMa2 7b) that uses an optimized transformer architecture. The chat version is fine-tuned on 180K instruction sets with the following trainables by using LoRA:
- **lr**=1e-4
- **lora_rank**=64
- **lora_alpha**=128
- **lora_trainable**=q_proj,v_proj,k_proj,o_proj,gate_proj,down_proj,up_proj
- **modules_to_save**=embed_tokens,lm_head
- **lora_dropout**=0.05
- **fp16**=True
- **max_seq_length**=1024
<img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/peft/lora_diagram.png"
alt="drawing" width="600"/>
## Usage
```python
from transformers import AutoModelForCausalLM, LlamaTokenizer, pipeline
model_id = "Trendyol/Trendyol-LLM-7b-chat-v0.1"
tokenizer = LlamaTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id,
device_map='auto',
load_in_8bit=True)
sampling_params = dict(do_sample=True, temperature=0.3, top_k=50, top_p=0.9)
pipe = pipeline("text-generation",
model=model,
tokenizer=tokenizer,
device_map="auto",
max_new_tokens=1024,
return_full_text=True,
repetition_penalty=1.1
)
DEFAULT_SYSTEM_PROMPT = "Sen yardımcı bir asistansın ve sana verilen talimatlar doğrultusunda en iyi cevabı üretmeye çalışacaksın.\n"
TEMPLATE = (
"[INST] <<SYS>>\n"
"{system_prompt}\n"
"<</SYS>>\n\n"
"{instruction} [/INST]"
)
def generate_prompt(instruction, system_prompt=DEFAULT_SYSTEM_PROMPT):
return TEMPLATE.format_map({'instruction': instruction,'system_prompt': system_prompt})
def generate_output(user_query, sys_prompt=DEFAULT_SYSTEM_PROMPT):
prompt = generate_prompt(user_query, sys_prompt)
outputs = pipe(prompt,
**sampling_params
)
return outputs[0]["generated_text"].split("[/INST]")[-1]
user_query = "Türkiye'de kaç il var?"
response = generate_output(user_query)
```
## Limitations, Risks, Bias, and Ethical Considerations
### Limitations and Known Biases
- **Primary Function and Application:** Trendyol LLM, an autoregressive language model, is primarily designed to predict the next token in a text string. While often used for various applications, it is important to note that it has not undergone extensive real-world application testing. Its effectiveness and reliability across diverse scenarios remain largely unverified.
- **Language Comprehension and Generation:** The model is primarily trained in standard English and Turkish. Its performance in understanding and generating slang, informal language, or other languages may be limited, leading to potential errors or misinterpretations.
- **Generation of False Information:** Users should be aware that Trendyol LLM may produce inaccurate or misleading information. Outputs should be considered as starting points or suggestions rather than definitive answers.
### Risks and Ethical Considerations
- **Potential for Harmful Use:** There is a risk that Trendyol LLM could be used to generate offensive or harmful language. We strongly discourage its use for any such purposes and emphasize the need for application-specific safety and fairness evaluations before deployment.
- **Unintended Content and Bias:** The model was trained on a large corpus of text data, which was not explicitly checked for offensive content or existing biases. Consequently, it may inadvertently produce content that reflects these biases or inaccuracies.
- **Toxicity:** Despite efforts to select appropriate training data, the model is capable of generating harmful content, especially when prompted explicitly. We encourage the open-source community to engage in developing strategies to minimize such risks.
### Recommendations for Safe and Ethical Usage
- **Human Oversight:** We recommend incorporating a human curation layer or using filters to manage and improve the quality of outputs, especially in public-facing applications. This approach can help mitigate the risk of generating objectionable content unexpectedly.
- **Application-Specific Testing:** Developers intending to use Trendyol LLM should conduct thorough safety testing and optimization tailored to their specific applications. This is crucial, as the models responses can be unpredictable and may occasionally be biased, inaccurate, or offensive.
- **Responsible Development and Deployment:** It is the responsibility of developers and users of Trendyol LLM to ensure its ethical and safe application. We urge users to be mindful of the model's limitations and to employ appropriate safeguards to prevent misuse or harmful consequences.

26
config.json Normal file
View File

@@ -0,0 +1,26 @@
{
"architectures": [
"LlamaForCausalLM"
],
"attention_bias": false,
"bos_token_id": 1,
"eos_token_id": 2,
"hidden_act": "silu",
"hidden_size": 4096,
"initializer_range": 0.02,
"intermediate_size": 11008,
"max_position_embeddings": 4096,
"model_type": "llama",
"num_attention_heads": 32,
"num_hidden_layers": 32,
"num_key_value_heads": 32,
"pretraining_tp": 1,
"rms_norm_eps": 1e-05,
"rope_scaling": null,
"rope_theta": 10000.0,
"tie_word_embeddings": false,
"torch_dtype": "float32",
"transformers_version": "4.35.0",
"use_cache": true,
"vocab_size": 44222
}

View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:f3c8722804696075024deeecdfa8390b12a46b794b85bcf0b7c29104ffb76fd7
size 2590659360

View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:c7d607d5eeca48b5450b95f5246746e5a6dc35e5ecc2a37148ba26e1de9f1711
size 3659991008

View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:346feddcc040b358e5e826ae086a99e1dec81e15a8374456c0a513e4d5d41871
size 3360884704

View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:d4653e68718b53a86ae06947b6f105eabaf386e931b6c25a931583697a06b83f
size 3011184608

View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:ef9f9a88162c97425c2afbe7ef149347098ecc79e6245d269aee16f2561028dc
size 3895335840

View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:323878a8570093178040e78b438d5670c0fdae2aa614a8ed58e784d697d4db52
size 4150533024

View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:e079bf671c7255c6a1a86e1cb5b349a7e7a48b042e10b0fbfda60a394ef6f66f
size 3926268832

View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:95f91382953091ee89c292dd3e15ea9ced3332df9243c4a3cddd558cac0f8c4d
size 4727478176

View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:abe74ad12996aaef9bb83a944b31c5a11e46063e75bf6df76102df369c0a9f29
size 4858943392

View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:3a4325f1d134ff7ff4626a34797ed8312a21f3f73cfab41a2ffb004d2b571aa5
size 4727478176

View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:7a440797034011a36bc099841b1c95b8de89e66cb6c165192a4dc9182c159932
size 5611629408

View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:b71e3715137eaf9467977e0b783b0b6ba1f8fbe56c4a6e980cae2a2433aae0e3
size 7267773408

View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:92d6f9a0213a401c0905a5cb69fa148592536bbf16764dcbd8e49b42281c043b
size 13678653376