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Model: prithivMLmods/Llama-8B-Distill-CoT Source: Original Platform
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README.md
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README.md
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---
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library_name: transformers
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license: llama3.1
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language:
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- en
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base_model:
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- deepseek-ai/DeepSeek-R1-Distill-Llama-8B
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pipeline_tag: text-generation
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tags:
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- llama
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- deepseek
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---
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# **Llama-8B-Distill-CoT**
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Llama-8B-Distill-CoT is based on the *Llama [ KT ]* model, distilled by DeepSeek-R1-Distill-Llama-8B. It has been fine-tuned on the long chain-of-thought reasoning model and specialized datasets, focusing on chain-of-thought (CoT) reasoning for problem-solving. This model is optimized for tasks requiring logical reasoning, detailed explanations, and multi-step problem-solving, making it ideal for applications such as instruction-following, text generation, and complex reasoning tasks.
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# **Use with transformers**
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Starting with `transformers >= 4.43.0` onward, you can run conversational inference using the Transformers `pipeline` abstraction or by leveraging the Auto classes with the `generate()` function.
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Make sure to update your transformers installation via `pip install --upgrade transformers`.
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```python
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import transformers
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import torch
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model_id = "prithivMLmods/Llama-8B-Distill-CoT"
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pipeline = transformers.pipeline(
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"text-generation",
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model=model_id,
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model_kwargs={"torch_dtype": torch.bfloat16},
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device_map="auto",
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)
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messages = [
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{"role": "system", "content": "You are a pirate chatbot who always responds in pirate speak!"},
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{"role": "user", "content": "Who are you?"},
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]
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outputs = pipeline(
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messages,
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max_new_tokens=256,
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)
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print(outputs[0]["generated_text"][-1])
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```
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### **Intended Use:**
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1. **Instruction-Following:** The model is designed to handle detailed instructions, making it ideal for virtual assistants, automation tools, and educational platforms.
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2. **Problem-Solving:** Its fine-tuning on chain-of-thought (CoT) reasoning allows it to tackle multi-step problem-solving in domains such as mathematics, logic, and programming.
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3. **Text Generation:** Capable of generating coherent and contextually relevant content, it is suitable for creative writing, documentation, and report generation.
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4. **Education and Training:** Provides step-by-step explanations and logical reasoning, making it a useful tool for teaching and learning.
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5. **Research and Analysis:** Supports researchers and professionals by generating detailed analyses and structured arguments for complex topics.
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6. **Programming Assistance:** Helps in generating, debugging, and explaining code, as well as creating structured outputs like JSON or XML.
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### **Limitations:**
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1. **Resource Intensive:** Requires high computational resources to run efficiently, which may limit accessibility for small-scale deployments.
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2. **Hallucination Risk:** May generate incorrect or misleading information, especially when handling ambiguous or poorly framed prompts.
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3. **Domain-Specific Gaps:** While fine-tuned for reasoning, it may not perform well in specialized domains outside its training data.
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4. **Bias in Training Data:** The model's responses can reflect biases present in the datasets it was trained on, potentially leading to biased or inappropriate outputs.
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5. **Dependence on Input Quality:** Performance heavily depends on clear, structured inputs. Ambiguous or vague queries can result in suboptimal outputs.
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6. **Limited Real-Time Context:** The model cannot access real-time information or updates beyond its training data, potentially affecting its relevance for time-sensitive queries.
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7. **Scalability for Long-Context:** While capable of multi-step reasoning, its ability to handle extremely long or complex contexts may be limited compared to larger, more specialized models.
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config.json
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config.json
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{
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"_name_or_path": "deepseek-ai/DeepSeek-R1-Distill-Llama-8B",
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"architectures": [
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"LlamaForCausalLM"
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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": 128000,
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"eos_token_id": 128001,
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"head_dim": 128,
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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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"mlp_bias": false,
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"model_type": "llama",
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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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"pad_token_id": 128004,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": {
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"factor": 8.0,
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"high_freq_factor": 4.0,
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"low_freq_factor": 1.0,
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"original_max_position_embeddings": 8192,
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"rope_type": "llama3"
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},
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"rope_theta": 500000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.47.1",
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"use_cache": true,
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"vocab_size": 128256
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}
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configuration.json
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"model.layers.9.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.norm.weight": "model-00004-of-00004.safetensors"
|
||||
}
|
||||
}
|
||||
23
special_tokens_map.json
Normal file
23
special_tokens_map.json
Normal file
@@ -0,0 +1,23 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<｜begin▁of▁sentence｜>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "<｜end▁of▁sentence｜>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": {
|
||||
"content": "<|finetune_right_pad_id|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:d91915040cfac999d8c55f4b5bc6e67367c065e3a7a4e4b9438ce1f256addd86
|
||||
size 17209530
|
||||
2068
tokenizer_config.json
Normal file
2068
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user