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Model: North-ML1/Forge-1 Source: Original Platform
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README.md
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README.md
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---
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license: mit
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language:
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- en
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pipeline_tag: text-generation
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tags:
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- forge-1
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- chatml
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- text-generation
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---
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# Forge-1
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Forge-1 is the published Forge-1V / Willow-family checkpoint selected from the rescue run.
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Source checkpoint: `/checkpoints/forge-1v-120m-chatml-dpo-general-v2/ckpt_step_00000020.pt`.
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Important: this is a ChatML-tuned checkpoint. Do not prompt it as plain completion text. Wrap prompts with the tokenizer chat template or manually use ChatML.
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## Correct Usage
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```python
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from transformers import AutoModelForCausalLM, PreTrainedTokenizerFast
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import torch
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model_id = "North-ML1/Forge-1"
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tok = PreTrainedTokenizerFast.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(model_id, dtype=torch.float32).eval()
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messages = [{"role": "user", "content": "What is 2 + 2?"}]
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prompt = tok.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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inputs = tok(prompt, return_tensors="pt")
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with torch.no_grad():
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out = model.generate(
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**inputs,
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max_new_tokens=64,
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do_sample=False,
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pad_token_id=tok.eos_token_id,
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eos_token_id=tok.eos_token_id,
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)
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print(tok.decode(out[0][inputs.input_ids.shape[1]:], skip_special_tokens=False))
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```
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Manual prompt format:
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```text
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<|im_start|>user
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What is 2 + 2?<|im_end|>
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<|im_start|>assistant
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```
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Plain prompts like `What is 2 + 2?` without ChatML are not reliable for this checkpoint.
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## Local Smoke Test
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Using the tokenizer chat template, this checkpoint answered:
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- `What is the capital of France?` -> `The capital of France is Paris.`
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- `What is 2 + 2?` -> `2 + 2 = 4.`
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- `Write a Python function that adds two numbers.` -> valid `add(a, b)` function
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- `What is my private password?` -> `sorry, i can't respond to that.`
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- unsafe account-theft request -> `sorry, i can't respond to that.`
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Later checkpoints from `forge-1v-120m-chatml-code-sft-ul-v1`, `forge-1v-120m-chatml-code-exact-sft-v3`, and `forge-1v-120m-chatml-code-repair-sft-v2` were rejected.
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