Text Generation
Transformers
Safetensors
GGUF
mistral
mergekit
Merge
conversational
text-generation-inference
Instructions to use MisterRaven006/SweetNeural-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MisterRaven006/SweetNeural-7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="MisterRaven006/SweetNeural-7B") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("MisterRaven006/SweetNeural-7B") model = AutoModelForMultimodalLM.from_pretrained("MisterRaven006/SweetNeural-7B") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - llama-cpp-python
How to use MisterRaven006/SweetNeural-7B with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="MisterRaven006/SweetNeural-7B", filename="SweetNeural-7B-Q5_K_M.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use MisterRaven006/SweetNeural-7B 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 MisterRaven006/SweetNeural-7B:Q4_K_M # Run inference directly in the terminal: llama cli -hf MisterRaven006/SweetNeural-7B:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf MisterRaven006/SweetNeural-7B:Q4_K_M # Run inference directly in the terminal: llama cli -hf MisterRaven006/SweetNeural-7B: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 MisterRaven006/SweetNeural-7B:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf MisterRaven006/SweetNeural-7B: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 MisterRaven006/SweetNeural-7B:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf MisterRaven006/SweetNeural-7B:Q4_K_M
Use Docker
docker model run hf.co/MisterRaven006/SweetNeural-7B:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use MisterRaven006/SweetNeural-7B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "MisterRaven006/SweetNeural-7B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "MisterRaven006/SweetNeural-7B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/MisterRaven006/SweetNeural-7B:Q4_K_M
- SGLang
How to use MisterRaven006/SweetNeural-7B with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "MisterRaven006/SweetNeural-7B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "MisterRaven006/SweetNeural-7B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "MisterRaven006/SweetNeural-7B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "MisterRaven006/SweetNeural-7B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Ollama
How to use MisterRaven006/SweetNeural-7B with Ollama:
ollama run hf.co/MisterRaven006/SweetNeural-7B:Q4_K_M
- Unsloth Studio
How to use MisterRaven006/SweetNeural-7B 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 MisterRaven006/SweetNeural-7B 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 MisterRaven006/SweetNeural-7B to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for MisterRaven006/SweetNeural-7B to start chatting
- Atomic Chat new
- Docker Model Runner
How to use MisterRaven006/SweetNeural-7B with Docker Model Runner:
docker model run hf.co/MisterRaven006/SweetNeural-7B:Q4_K_M
- Lemonade
How to use MisterRaven006/SweetNeural-7B with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull MisterRaven006/SweetNeural-7B:Q4_K_M
Run and chat with the model
lemonade run user.SweetNeural-7B-Q4_K_M
List all available models
lemonade list
Upload folder using huggingface_hub
Browse files- README.md +47 -0
- config.json +26 -0
- mergekit_config.yml +16 -0
- model-00001-of-00002.safetensors +3 -0
- model-00002-of-00002.safetensors +3 -0
- model.safetensors.index.json +1 -0
- special_tokens_map.json +35 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +49 -0
README.md
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---
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base_model:
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- KatyTheCutie/LemonadeRP-4.5.3
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- mlabonne/NeuralBeagle14-7B
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library_name: transformers
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tags:
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- mergekit
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- merge
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---
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# merge
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
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## Merge Details
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### Merge Method
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This model was merged using the SLERP merge method.
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### Models Merged
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The following models were included in the merge:
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* [KatyTheCutie/LemonadeRP-4.5.3](https://huggingface.co/KatyTheCutie/LemonadeRP-4.5.3)
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* [mlabonne/NeuralBeagle14-7B](https://huggingface.co/mlabonne/NeuralBeagle14-7B)
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### Configuration
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The following YAML configuration was used to produce this model:
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```yaml
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slices:
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- sources:
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- model: mlabonne/NeuralBeagle14-7B
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layer_range: [0, 32]
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- model: KatyTheCutie/LemonadeRP-4.5.3
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layer_range: [0, 32]
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merge_method: slerp
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base_model: mlabonne/NeuralBeagle14-7B
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parameters:
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t:
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- filter: self_attn
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value: [0, 0.5, 0.3, 0.7, 1]
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- filter: mlp
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value: [1, 0.5, 0.7, 0.3, 0]
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- value: 0.5
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dtype: bfloat16
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```
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config.json
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{
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"_name_or_path": "mlabonne/NeuralBeagle14-7B",
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"architectures": [
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"MistralForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 14336,
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"max_position_embeddings": 32768,
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"model_type": "mistral",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"rms_norm_eps": 1e-05,
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"rope_theta": 10000.0,
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"sliding_window": 4096,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.39.3",
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"use_cache": false,
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"vocab_size": 32000
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}
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mergekit_config.yml
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slices:
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- sources:
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| 3 |
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- model: mlabonne/NeuralBeagle14-7B
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layer_range: [0, 32]
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- model: KatyTheCutie/LemonadeRP-4.5.3
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layer_range: [0, 32]
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merge_method: slerp
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base_model: mlabonne/NeuralBeagle14-7B
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parameters:
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t:
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- filter: self_attn
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value: [0, 0.5, 0.3, 0.7, 1]
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+
- filter: mlp
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value: [1, 0.5, 0.7, 0.3, 0]
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| 15 |
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- value: 0.5
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dtype: bfloat16
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model-00001-of-00002.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:a7f973f0b3f057e1eca64cbb07281ef777707ccce14b132288b4724e6a4e88eb
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size 9942981696
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model-00002-of-00002.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:74a82b155b80fe0ff753b59adc931d8c1f182378d09f511c4fd4ed1d24e7cc62
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size 4540516344
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model.safetensors.index.json
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{"metadata": {"mergekit_version": "0.0.4.2", "total_size": 14483464192}, "weight_map": {"model.layers.10.mlp.gate_proj.weight": "model-00001-of-00002.safetensors", "model.layers.10.mlp.up_proj.weight": "model-00001-of-00002.safetensors", "model.layers.10.self_attn.o_proj.weight": "model-00001-of-00002.safetensors", "model.layers.10.self_attn.v_proj.weight": "model-00001-of-00002.safetensors", "model.layers.10.self_attn.k_proj.weight": "model-00001-of-00002.safetensors", "model.layers.10.self_attn.q_proj.weight": "model-00001-of-00002.safetensors", "model.layers.9.mlp.down_proj.weight": "model-00001-of-00002.safetensors", "model.layers.9.mlp.gate_proj.weight": "model-00001-of-00002.safetensors", "model.layers.9.mlp.up_proj.weight": "model-00001-of-00002.safetensors", "model.layers.9.post_attention_layernorm.weight": "model-00001-of-00002.safetensors", "model.layers.9.self_attn.o_proj.weight": "model-00001-of-00002.safetensors", "model.layers.9.self_attn.v_proj.weight": 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{
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| 2 |
+
"additional_special_tokens": [
|
| 3 |
+
"<unk>",
|
| 4 |
+
"<s>",
|
| 5 |
+
"</s>"
|
| 6 |
+
],
|
| 7 |
+
"bos_token": {
|
| 8 |
+
"content": "<s>",
|
| 9 |
+
"lstrip": false,
|
| 10 |
+
"normalized": false,
|
| 11 |
+
"rstrip": false,
|
| 12 |
+
"single_word": false
|
| 13 |
+
},
|
| 14 |
+
"eos_token": {
|
| 15 |
+
"content": "</s>",
|
| 16 |
+
"lstrip": false,
|
| 17 |
+
"normalized": false,
|
| 18 |
+
"rstrip": false,
|
| 19 |
+
"single_word": false
|
| 20 |
+
},
|
| 21 |
+
"pad_token": {
|
| 22 |
+
"content": "</s>",
|
| 23 |
+
"lstrip": false,
|
| 24 |
+
"normalized": false,
|
| 25 |
+
"rstrip": false,
|
| 26 |
+
"single_word": false
|
| 27 |
+
},
|
| 28 |
+
"unk_token": {
|
| 29 |
+
"content": "<unk>",
|
| 30 |
+
"lstrip": false,
|
| 31 |
+
"normalized": false,
|
| 32 |
+
"rstrip": false,
|
| 33 |
+
"single_word": false
|
| 34 |
+
}
|
| 35 |
+
}
|
tokenizer.json
ADDED
|
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|
|
|
tokenizer.model
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
|
| 3 |
+
size 493443
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,49 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_bos_token": true,
|
| 3 |
+
"add_eos_token": false,
|
| 4 |
+
"added_tokens_decoder": {
|
| 5 |
+
"0": {
|
| 6 |
+
"content": "<unk>",
|
| 7 |
+
"lstrip": false,
|
| 8 |
+
"normalized": false,
|
| 9 |
+
"rstrip": false,
|
| 10 |
+
"single_word": false,
|
| 11 |
+
"special": true
|
| 12 |
+
},
|
| 13 |
+
"1": {
|
| 14 |
+
"content": "<s>",
|
| 15 |
+
"lstrip": false,
|
| 16 |
+
"normalized": false,
|
| 17 |
+
"rstrip": false,
|
| 18 |
+
"single_word": false,
|
| 19 |
+
"special": true
|
| 20 |
+
},
|
| 21 |
+
"2": {
|
| 22 |
+
"content": "</s>",
|
| 23 |
+
"lstrip": false,
|
| 24 |
+
"normalized": false,
|
| 25 |
+
"rstrip": false,
|
| 26 |
+
"single_word": false,
|
| 27 |
+
"special": true
|
| 28 |
+
}
|
| 29 |
+
},
|
| 30 |
+
"additional_special_tokens": [
|
| 31 |
+
"<unk>",
|
| 32 |
+
"<s>",
|
| 33 |
+
"</s>"
|
| 34 |
+
],
|
| 35 |
+
"bos_token": "<s>",
|
| 36 |
+
"chat_template": "{% for message in messages %}{{bos_token + message['role'] + '\n' + message['content'] + eos_token + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ bos_token + 'assistant\n' }}{% endif %}",
|
| 37 |
+
"clean_up_tokenization_spaces": false,
|
| 38 |
+
"eos_token": "</s>",
|
| 39 |
+
"legacy": true,
|
| 40 |
+
"model_max_length": 8192,
|
| 41 |
+
"pad_token": "</s>",
|
| 42 |
+
"padding_side": "left",
|
| 43 |
+
"sp_model_kwargs": {},
|
| 44 |
+
"spaces_between_special_tokens": false,
|
| 45 |
+
"split_special_tokens": false,
|
| 46 |
+
"tokenizer_class": "LlamaTokenizer",
|
| 47 |
+
"unk_token": "<unk>",
|
| 48 |
+
"use_default_system_prompt": true
|
| 49 |
+
}
|