Text Generation
Transformers
Safetensors
mixtral
Mixture of Experts
frankenmoe
Merge
mergekit
lazymergekit
TinyLlama/TinyLlama-1.1B-Chat-v1.0
h4rz3rk4s3/TinyNewsLlama-1.1B
h4rz3rk4s3/TinyParlaMintLlama-1.1B
conversational
text-generation-inference
Instructions to use h4rz3rk4s3/TinyPoliticaLlama-3x1.1B-nf4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use h4rz3rk4s3/TinyPoliticaLlama-3x1.1B-nf4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="h4rz3rk4s3/TinyPoliticaLlama-3x1.1B-nf4") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("h4rz3rk4s3/TinyPoliticaLlama-3x1.1B-nf4") model = AutoModelForCausalLM.from_pretrained("h4rz3rk4s3/TinyPoliticaLlama-3x1.1B-nf4", device_map="auto") 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]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use h4rz3rk4s3/TinyPoliticaLlama-3x1.1B-nf4 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "h4rz3rk4s3/TinyPoliticaLlama-3x1.1B-nf4" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "h4rz3rk4s3/TinyPoliticaLlama-3x1.1B-nf4", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/h4rz3rk4s3/TinyPoliticaLlama-3x1.1B-nf4
- SGLang
How to use h4rz3rk4s3/TinyPoliticaLlama-3x1.1B-nf4 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 "h4rz3rk4s3/TinyPoliticaLlama-3x1.1B-nf4" \ --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": "h4rz3rk4s3/TinyPoliticaLlama-3x1.1B-nf4", "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 "h4rz3rk4s3/TinyPoliticaLlama-3x1.1B-nf4" \ --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": "h4rz3rk4s3/TinyPoliticaLlama-3x1.1B-nf4", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use h4rz3rk4s3/TinyPoliticaLlama-3x1.1B-nf4 with Docker Model Runner:
docker model run hf.co/h4rz3rk4s3/TinyPoliticaLlama-3x1.1B-nf4
Upload folder using huggingface_hub
Browse files- README.md +61 -0
- config.json +33 -0
- mergekit_moe_config.yml +11 -0
- model-00001-of-00001.safetensors +3 -0
- model.safetensors.index.json +1 -0
- special_tokens_map.json +24 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +42 -0
README.md
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---
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license: apache-2.0
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tags:
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- moe
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- frankenmoe
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- merge
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- mergekit
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- lazymergekit
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- TinyLlama/TinyLlama-1.1B-Chat-v1.0
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- h4rz3rk4s3/TinyNewsLlama-1.1B
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- h4rz3rk4s3/TinyParlaMintLlama-1.1B
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base_model:
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- TinyLlama/TinyLlama-1.1B-Chat-v1.0
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- h4rz3rk4s3/TinyNewsLlama-1.1B
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- h4rz3rk4s3/TinyParlaMintLlama-1.1B
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---
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# TinyPoliticaLlama-3x1.1B-nf4
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TinyPoliticaLlama-3x1.1B-nf4 is a Mixure of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
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* [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0)
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* [h4rz3rk4s3/TinyNewsLlama-1.1B](https://huggingface.co/h4rz3rk4s3/TinyNewsLlama-1.1B)
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* [h4rz3rk4s3/TinyParlaMintLlama-1.1B](https://huggingface.co/h4rz3rk4s3/TinyParlaMintLlama-1.1B)
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## 🧩 Configuration
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```yaml
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base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
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dtype: float16
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gate_mode: cheap_embed
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experts:
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- source_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
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positive_prompts: ["chat", "assistant", "tell me", "explain"]
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- source_model: h4rz3rk4s3/TinyNewsLlama-1.1B
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positive_prompts: ["news", "USA", "politics", "journalism", "write"]
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- source_model: h4rz3rk4s3/TinyParlaMintLlama-1.1B
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positive_prompts: ["speech", "politics", "EU", "europe", "write"]```
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## 💻 Usage
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```python
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!pip install -qU transformers bitsandbytes accelerate
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from transformers import AutoTokenizer
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import transformers
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import torch
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model = "h4rz3rk4s3/TinyPoliticaLlama-3x1.1B-nf4"
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tokenizer = AutoTokenizer.from_pretrained(model)
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pipeline = transformers.pipeline(
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"text-generation",
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model=model,
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model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
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)
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messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}]
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prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
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print(outputs[0]["generated_text"])
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```
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config.json
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{
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"_name_or_path": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
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"architectures": [
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"MixtralForCausalLM"
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],
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"attention_bias": false,
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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": 2048,
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"initializer_range": 0.02,
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"intermediate_size": 5632,
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"max_position_embeddings": 2048,
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"model_type": "mixtral",
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"num_attention_heads": 32,
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"num_experts_per_tok": 2,
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"num_hidden_layers": 22,
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"num_key_value_heads": 4,
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"num_local_experts": 3,
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"output_router_logits": false,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": null,
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"rope_theta": 10000.0,
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"router_aux_loss_coef": 0.001,
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"sliding_window": null,
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"tie_word_embeddings": false,
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"torch_dtype": "float16",
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"transformers_version": "4.37.2",
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"use_cache": true,
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"vocab_size": 32000
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}
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mergekit_moe_config.yml
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base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
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dtype: float16
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gate_mode: cheap_embed
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experts:
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- source_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
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positive_prompts: ["chat", "assistant", "tell me", "explain"]
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- source_model: h4rz3rk4s3/TinyNewsLlama-1.1B
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positive_prompts: ["news", "USA", "politics", "journalism", "write"]
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- source_model: h4rz3rk4s3/TinyParlaMintLlama-1.1B
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positive_prompts: ["speech", "politics", "EU", "europe", "write"]
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model-00001-of-00001.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:994f5e8c581d3debecdd499759afa58adafd499b2a03a60cc815a0288f0c5953
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size 3722943168
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model.safetensors.index.json
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{"metadata": {"mergekit_version": "0.0.4"}, "weight_map": {"model.embed_tokens.weight": "model-00001-of-00001.safetensors", "model.norm.weight": "model-00001-of-00001.safetensors", "lm_head.weight": "model-00001-of-00001.safetensors", "model.layers.0.input_layernorm.weight": "model-00001-of-00001.safetensors", "model.layers.1.input_layernorm.weight": "model-00001-of-00001.safetensors", "model.layers.2.input_layernorm.weight": "model-00001-of-00001.safetensors", "model.layers.3.input_layernorm.weight": "model-00001-of-00001.safetensors", "model.layers.4.input_layernorm.weight": "model-00001-of-00001.safetensors", "model.layers.5.input_layernorm.weight": "model-00001-of-00001.safetensors", "model.layers.6.input_layernorm.weight": "model-00001-of-00001.safetensors", "model.layers.7.input_layernorm.weight": "model-00001-of-00001.safetensors", "model.layers.8.input_layernorm.weight": "model-00001-of-00001.safetensors", "model.layers.9.input_layernorm.weight": 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special_tokens_map.json
ADDED
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{
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| 2 |
+
"bos_token": {
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| 3 |
+
"content": "<s>",
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| 4 |
+
"lstrip": false,
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| 5 |
+
"normalized": false,
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| 6 |
+
"rstrip": false,
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| 7 |
+
"single_word": false
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| 8 |
+
},
|
| 9 |
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"eos_token": {
|
| 10 |
+
"content": "</s>",
|
| 11 |
+
"lstrip": false,
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| 12 |
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"normalized": false,
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| 13 |
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"rstrip": false,
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| 14 |
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"single_word": false
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| 15 |
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},
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| 16 |
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"pad_token": "<s>",
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| 17 |
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"unk_token": {
|
| 18 |
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"content": "<unk>",
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| 19 |
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"lstrip": false,
|
| 20 |
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"normalized": false,
|
| 21 |
+
"rstrip": false,
|
| 22 |
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"single_word": false
|
| 23 |
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}
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| 24 |
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}
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tokenizer.json
ADDED
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tokenizer.model
ADDED
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+
version https://git-lfs.github.com/spec/v1
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oid sha256:9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347
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| 3 |
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size 499723
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tokenizer_config.json
ADDED
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+
{
|
| 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,
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| 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 |
+
"bos_token": "<s>",
|
| 31 |
+
"chat_template": "{% for message in messages %}\n{% if message['role'] == 'user' %}\n{{ '<|user|>\n' + message['content'] + eos_token }}\n{% elif message['role'] == 'system' %}\n{{ '<|system|>\n' + message['content'] + eos_token }}\n{% elif message['role'] == 'assistant' %}\n{{ '<|assistant|>\n' + message['content'] + eos_token }}\n{% endif %}\n{% if loop.last and add_generation_prompt %}\n{{ '<|assistant|>' }}\n{% endif %}\n{% endfor %}",
|
| 32 |
+
"clean_up_tokenization_spaces": false,
|
| 33 |
+
"eos_token": "</s>",
|
| 34 |
+
"legacy": false,
|
| 35 |
+
"model_max_length": 2048,
|
| 36 |
+
"pad_token": "<s>",
|
| 37 |
+
"padding_side": "left",
|
| 38 |
+
"sp_model_kwargs": {},
|
| 39 |
+
"tokenizer_class": "LlamaTokenizer",
|
| 40 |
+
"unk_token": "<unk>",
|
| 41 |
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"use_default_system_prompt": false
|
| 42 |
+
}
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